{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S20_S27_FE_PoissonCRE.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Apr 2024, 11:10:21
{txt}
{com}. use  NER_panel_data.dta, clear
{txt}
{com}. gen country=1
{txt}
{com}. append using NIGERIA_panel_data.dta
{txt}
{com}. replace country=2 if country ==.
{txt}(18,592 real changes made)

{com}. 
. append using ETHIOPIA_panel_data.dta
{txt}
{com}. replace country=3 if country ==.
{txt}(13,511 real changes made)

{com}. 
. append using UGA_panel_data.dta
{txt}
{com}. replace country=4 if country ==.
{txt}(20,313 real changes made)

{com}. 
. append using TZA_panel_data.dta
{txt}
{com}. replace country=5 if country ==.
{txt}(21,117 real changes made)

{com}. 
. append using MWI_panel_data.dta
{txt}
{com}. replace country=6 if country ==.
{txt}(9,163 real changes made)

{com}. 
. xtset HHID_panel year
{res}{txt}{col 8}panel variable:  {res}HHID_panel (unbalanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2008 to 2019, but with gaps
{txt}{col 17}delta:  {res}1 unit
{txt}
{com}. 
. label define country 1 "Niger" 2 "Nigeria" 3 "Ethiopia" 4 "Uganda" 5 "Tanzania" 6 "Malawi"
{txt}
{com}. label values country country
{txt}
{com}. 
. tab year, generate(year_)

       {txt}year {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
       2008 {c |}{res}      3,176        3.54        3.54
{txt}       2009 {c |}{res}      2,837        3.16        6.70
{txt}       2010 {c |}{res}     12,719       14.17       20.87
{txt}       2011 {c |}{res}     10,467       11.66       32.54
{txt}       2012 {c |}{res}      9,429       10.51       43.04
{txt}       2013 {c |}{res}     10,027       11.17       54.22
{txt}       2014 {c |}{res}      7,298        8.13       62.35
{txt}       2015 {c |}{res}     12,323       13.73       76.08
{txt}       2016 {c |}{res}      2,447        2.73       78.81
{txt}       2018 {c |}{res}      7,615        8.49       87.29
{txt}       2019 {c |}{res}     11,404       12.71      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     89,742      100.00
{txt}
{com}. global year_NIGER year_4
{txt}
{com}. global year_NIGERIA year_3 year_5 year_8
{txt}
{com}. global year_ETHIOPIA year_6
{txt}
{com}. global year_UGANDA   year_3 year_4 year_6 year_8 year_10
{txt}
{com}. global year_TANZANIA year_1 year_5 year_7
{txt}
{com}. global year_MALAWI year_3 year_6 
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop
{txt}
{com}. 
. 
. ********************************************************************************
. *                                   S20                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  no_species   $xlist    i.year  , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    89,742
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    36,644

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0335{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0817{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.0648{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}24{txt},{res}36643{txt}){col 67}={col 70}{res}    70.03
{txt}corr(u_i, Xb){col 16}= {res}0.0759{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2} .0482156{col 29}{space 2}  .002933{col 40}{space 1}   16.44{col 49}{space 3}0.000{col 57}{space 4} .0424668{col 70}{space 3} .0539643
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0234238{col 29}{space 2} .0042912{col 40}{space 1}    5.46{col 49}{space 3}0.000{col 57}{space 4}  .015013{col 70}{space 3} .0318346
{txt}dependent_share {c |}{col 17}{res}{space 2} .1048031{col 29}{space 2}  .037252{col 40}{space 1}    2.81{col 49}{space 3}0.005{col 57}{space 4} .0317881{col 70}{space 3} .1778181
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0036075{col 29}{space 2} .0011556{col 40}{space 1}   -3.12{col 49}{space 3}0.002{col 57}{space 4}-.0058725{col 70}{space 3}-.0013424
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1007426{col 29}{space 2}   .03004{col 40}{space 1}   -3.35{col 49}{space 3}0.001{col 57}{space 4}-.1596218{col 70}{space 3}-.0418634
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0858183{col 29}{space 2} .0201197{col 40}{space 1}    4.27{col 49}{space 3}0.000{col 57}{space 4} .0463831{col 70}{space 3} .1252534
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1117257{col 29}{space 2} .0252043{col 40}{space 1}    4.43{col 49}{space 3}0.000{col 57}{space 4} .0623246{col 70}{space 3} .1611268
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1888163{col 29}{space 2} .0174378{col 40}{space 1}   10.83{col 49}{space 3}0.000{col 57}{space 4} .1546377{col 70}{space 3} .2229948
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1550711{col 29}{space 2} .0201767{col 40}{space 1}    7.69{col 49}{space 3}0.000{col 57}{space 4} .1155241{col 70}{space 3} .1946181
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1187862{col 29}{space 2} .0166519{col 40}{space 1}    7.13{col 49}{space 3}0.000{col 57}{space 4} .0861481{col 70}{space 3} .1514244
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2121742{col 29}{space 2} .0155919{col 40}{space 1}   13.61{col 49}{space 3}0.000{col 57}{space 4} .1816136{col 70}{space 3} .2427347
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0384578{col 29}{space 2}  .015521{col 40}{space 1}    2.48{col 49}{space 3}0.013{col 57}{space 4} .0080361{col 70}{space 3} .0688795
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0036871{col 29}{space 2} .0013059{col 40}{space 1}    2.82{col 49}{space 3}0.005{col 57}{space 4} .0011274{col 70}{space 3} .0062468
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0639375{col 29}{space 2} .0219611{col 40}{space 1}   -2.91{col 49}{space 3}0.004{col 57}{space 4}-.1069819{col 70}{space 3} -.020893
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2} -.148863{col 29}{space 2} .0410212{col 40}{space 1}   -3.63{col 49}{space 3}0.000{col 57}{space 4}-.2292657{col 70}{space 3}-.0684604
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .0505552{col 29}{space 2} .0289668{col 40}{space 1}    1.75{col 49}{space 3}0.081{col 57}{space 4}-.0062206{col 70}{space 3} .1073309
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2493523{col 29}{space 2} .0352355{col 40}{space 1}    7.08{col 49}{space 3}0.000{col 57}{space 4} .1802897{col 70}{space 3} .3184148
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0822002{col 29}{space 2} .0298111{col 40}{space 1}    2.76{col 49}{space 3}0.006{col 57}{space 4} .0237696{col 70}{space 3} .1406307
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2481316{col 29}{space 2} .0350504{col 40}{space 1}    7.08{col 49}{space 3}0.000{col 57}{space 4} .1794317{col 70}{space 3} .3168315
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .2381504{col 29}{space 2} .0394053{col 40}{space 1}    6.04{col 49}{space 3}0.000{col 57}{space 4} .1609148{col 70}{space 3}  .315386
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3270794{col 29}{space 2} .0336359{col 40}{space 1}    9.72{col 49}{space 3}0.000{col 57}{space 4} .2611522{col 70}{space 3} .3930066
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0166551{col 29}{space 2} .0465314{col 40}{space 1}   -0.36{col 49}{space 3}0.720{col 57}{space 4} -.107858{col 70}{space 3} .0745479
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .5656404{col 29}{space 2}   .03933{col 40}{space 1}   14.38{col 49}{space 3}0.000{col 57}{space 4} .4885526{col 70}{space 3} .6427283
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .2615253{col 29}{space 2} .0383036{col 40}{space 1}    6.83{col 49}{space 3}0.000{col 57}{space 4} .1864493{col 70}{space 3} .3366014
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.885528{col 29}{space 2}  .065695{col 40}{space 1}   74.37{col 49}{space 3}0.000{col 57}{space 4} 4.756764{col 70}{space 3} 5.014292
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4866522
        {txt}sigma_e {c |} {res} 1.2559737
            {txt}rho {c |} {res} .58351778{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    13,511
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,436

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0307{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0567{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0548{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}15{txt},{res}5435{txt}){col 67}={col 70}{res}    16.56
{txt}corr(u_i, Xb){col 16}= {res}0.0355{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2}  .025872{col 29}{space 2} .0057174{col 40}{space 1}    4.53{col 49}{space 3}0.000{col 57}{space 4} .0146637{col 70}{space 3} .0370803
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0595284{col 29}{space 2} .0126151{col 40}{space 1}    4.72{col 49}{space 3}0.000{col 57}{space 4} .0347977{col 70}{space 3}  .084259
{txt}dependent_share {c |}{col 17}{res}{space 2} -.117709{col 29}{space 2} .0908423{col 40}{space 1}   -1.30{col 49}{space 3}0.195{col 57}{space 4}-.2957962{col 70}{space 3} .0603782
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0092301{col 29}{space 2} .0027574{col 40}{space 1}    3.35{col 49}{space 3}0.001{col 57}{space 4} .0038245{col 70}{space 3} .0146357
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0283914{col 29}{space 2} .0783305{col 40}{space 1}   -0.36{col 49}{space 3}0.717{col 57}{space 4}-.1819505{col 70}{space 3} .1251677
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1891966{col 29}{space 2} .0455735{col 40}{space 1}    4.15{col 49}{space 3}0.000{col 57}{space 4} .0998543{col 70}{space 3}  .278539
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1108647{col 29}{space 2} .1307817{col 40}{space 1}   -0.85{col 49}{space 3}0.397{col 57}{space 4}-.3672492{col 70}{space 3} .1455199
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1855654{col 29}{space 2}  .036978{col 40}{space 1}    5.02{col 49}{space 3}0.000{col 57}{space 4} .1130738{col 70}{space 3}  .258057
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1107163{col 29}{space 2} .0449031{col 40}{space 1}    2.47{col 49}{space 3}0.014{col 57}{space 4} .0226883{col 70}{space 3} .1987444
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0310039{col 29}{space 2} .0536122{col 40}{space 1}   -0.58{col 49}{space 3}0.563{col 57}{space 4}-.1361053{col 70}{space 3} .0740976
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2125716{col 29}{space 2} .0471152{col 40}{space 1}    4.51{col 49}{space 3}0.000{col 57}{space 4}  .120207{col 70}{space 3} .3049362
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0033244{col 29}{space 2} .0355843{col 40}{space 1}   -0.09{col 49}{space 3}0.926{col 57}{space 4}-.0730838{col 70}{space 3}  .066435
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0108897{col 29}{space 2} .0044392{col 40}{space 1}    2.45{col 49}{space 3}0.014{col 57}{space 4} .0021871{col 70}{space 3} .0195923
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0082331{col 29}{space 2} .0478008{col 40}{space 1}   -0.17{col 49}{space 3}0.863{col 57}{space 4}-.1019417{col 70}{space 3} .0854756
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.2011964{col 29}{space 2} .0221684{col 40}{space 1}   -9.08{col 49}{space 3}0.000{col 57}{space 4}-.2446554{col 70}{space 3}-.1577373
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 3.429231{col 29}{space 2} .1424224{col 40}{space 1}   24.08{col 49}{space 3}0.000{col 57}{space 4} 3.150026{col 70}{space 3} 3.708436
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3191589
        {txt}sigma_e {c |} {res} 1.1132581
            {txt}rho {c |} {res} .58404639{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist   $year_MALAWI if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     9,163
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,447

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0443{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2819{col 63}{txt}avg{col 67}={col 69}{res}       2.7
{txt}     overall = {res}0.2137{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}16{txt},{res}3446{txt}){col 67}={col 70}{res}    15.84
{txt}corr(u_i, Xb){col 16}= {res}0.3185{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2} .0844236{col 29}{space 2} .0103251{col 40}{space 1}    8.18{col 49}{space 3}0.000{col 57}{space 4} .0641797{col 70}{space 3} .1046676
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0118067{col 29}{space 2} .0137614{col 40}{space 1}    0.86{col 49}{space 3}0.391{col 57}{space 4}-.0151747{col 70}{space 3} .0387881
{txt}dependent_share {c |}{col 17}{res}{space 2}-.3163198{col 29}{space 2}  .099683{col 40}{space 1}   -3.17{col 49}{space 3}0.002{col 57}{space 4}-.5117636{col 70}{space 3}-.1208761
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0013028{col 29}{space 2} .0030917{col 40}{space 1}   -0.42{col 49}{space 3}0.673{col 57}{space 4}-.0073646{col 70}{space 3}  .004759
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1140578{col 29}{space 2} .0673747{col 40}{space 1}   -1.69{col 49}{space 3}0.091{col 57}{space 4}-.2461561{col 70}{space 3} .0180406
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1515419{col 29}{space 2} .0618221{col 40}{space 1}    2.45{col 49}{space 3}0.014{col 57}{space 4} .0303302{col 70}{space 3} .2727535
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2342372{col 29}{space 2} .1351176{col 40}{space 1}    1.73{col 49}{space 3}0.083{col 57}{space 4}-.0306815{col 70}{space 3}  .499156
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2597337{col 29}{space 2} .0527145{col 40}{space 1}    4.93{col 49}{space 3}0.000{col 57}{space 4} .1563788{col 70}{space 3} .3630886
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .4517668{col 29}{space 2} .0857927{col 40}{space 1}    5.27{col 49}{space 3}0.000{col 57}{space 4} .2835572{col 70}{space 3} .6199764
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1776997{col 29}{space 2} .0563321{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 57}{space 4}  .067252{col 70}{space 3} .2881473
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2615961{col 29}{space 2}  .041542{col 40}{space 1}    6.30{col 49}{space 3}0.000{col 57}{space 4} .1801467{col 70}{space 3} .3430455
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1135765{col 29}{space 2} .0389775{col 40}{space 1}   -2.91{col 49}{space 3}0.004{col 57}{space 4}-.1899979{col 70}{space 3}-.0371551
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0120406{col 29}{space 2} .0362282{col 40}{space 1}    0.33{col 49}{space 3}0.740{col 57}{space 4}-.0589903{col 70}{space 3} .0830716
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0175674{col 29}{space 2} .0622892{col 40}{space 1}    0.28{col 49}{space 3}0.778{col 57}{space 4}-.1045601{col 70}{space 3} .1396948
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .1562092{col 29}{space 2}  .049606{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 57}{space 4} .0589492{col 70}{space 3} .2534693
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .0811219{col 29}{space 2} .0388875{col 40}{space 1}    2.09{col 49}{space 3}0.037{col 57}{space 4}  .004877{col 70}{space 3} .1573668
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.637606{col 29}{space 2} .1668159{col 40}{space 1}   33.80{col 49}{space 3}0.000{col 57}{space 4} 5.310538{col 70}{space 3} 5.964674
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3185823
        {txt}sigma_e {c |} {res} 1.3052971
            {txt}rho {c |} {res} .50506304{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     7,046
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,069

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0543{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0001{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0033{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}15{txt},{res}4068{txt}){col 67}={col 70}{res}    10.47
{txt}corr(u_i, Xb){col 16}= {res}-0.2191{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2}  .144211{col 29}{space 2} .0176492{col 40}{space 1}    8.17{col 49}{space 3}0.000{col 57}{space 4} .1096088{col 70}{space 3} .1788131
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0490434{col 29}{space 2}  .017231{col 40}{space 1}   -2.85{col 49}{space 3}0.004{col 57}{space 4}-.0828255{col 70}{space 3}-.0152612
{txt}dependent_share {c |}{col 17}{res}{space 2}  .122882{col 29}{space 2} .2225964{col 40}{space 1}    0.55{col 49}{space 3}0.581{col 57}{space 4}-.3135289{col 70}{space 3} .5592928
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}  .006701{col 29}{space 2} .0055838{col 40}{space 1}    1.20{col 49}{space 3}0.230{col 57}{space 4}-.0042463{col 70}{space 3} .0176484
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .2714948{col 29}{space 2}  .151778{col 40}{space 1}    1.79{col 49}{space 3}0.074{col 57}{space 4}-.0260732{col 70}{space 3} .5690627
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}  .168552{col 29}{space 2} .0825222{col 40}{space 1}    2.04{col 49}{space 3}0.041{col 57}{space 4} .0067633{col 70}{space 3} .3303406
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2737782{col 29}{space 2} .0962637{col 40}{space 1}    2.84{col 49}{space 3}0.004{col 57}{space 4} .0850486{col 70}{space 3} .4625079
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1242091{col 29}{space 2} .0739762{col 40}{space 1}    1.68{col 49}{space 3}0.093{col 57}{space 4}-.0208248{col 70}{space 3} .2692429
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2282767{col 29}{space 2} .1057281{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} .0209917{col 70}{space 3} .4355617
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2122453{col 29}{space 2} .0845182{col 40}{space 1}    2.51{col 49}{space 3}0.012{col 57}{space 4} .0465433{col 70}{space 3} .3779472
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1842557{col 29}{space 2} .0651061{col 40}{space 1}   -2.83{col 49}{space 3}0.005{col 57}{space 4}-.3118993{col 70}{space 3} -.056612
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0101329{col 29}{space 2} .0661038{col 40}{space 1}    0.15{col 49}{space 3}0.878{col 57}{space 4}-.1194667{col 70}{space 3} .1397325
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0049701{col 29}{space 2} .0026426{col 40}{space 1}    1.88{col 49}{space 3}0.060{col 57}{space 4}-.0002109{col 70}{space 3} .0101511
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0547517{col 29}{space 2} .3553774{col 40}{space 1}   -0.15{col 49}{space 3}0.878{col 57}{space 4}-.7514859{col 70}{space 3} .6419825
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}   .29802{col 29}{space 2} .0420352{col 40}{space 1}    7.09{col 49}{space 3}0.000{col 57}{space 4} .2156081{col 70}{space 3}  .380432
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.761648{col 29}{space 2} .3135524{col 40}{space 1}   15.19{col 49}{space 3}0.000{col 57}{space 4} 4.146914{col 70}{space 3} 5.376382
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4854364
        {txt}sigma_e {c |} {res} 1.3666293
            {txt}rho {c |} {res} .54158436{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    18,592
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,222

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0467{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0533{col 63}{txt}avg{col 67}={col 69}{res}       2.3
{txt}     overall = {res}0.0456{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}8221{txt}){col 67}={col 70}{res}    26.92
{txt}corr(u_i, Xb){col 16}= {res}-0.0076{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2} .0449225{col 29}{space 2} .0082618{col 40}{space 1}    5.44{col 49}{space 3}0.000{col 57}{space 4} .0287272{col 70}{space 3} .0611177
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0238836{col 29}{space 2} .0090202{col 40}{space 1}    2.65{col 49}{space 3}0.008{col 57}{space 4} .0062017{col 70}{space 3} .0415655
{txt}dependent_share {c |}{col 17}{res}{space 2}   .16995{col 29}{space 2} .0778354{col 40}{space 1}    2.18{col 49}{space 3}0.029{col 57}{space 4}  .017373{col 70}{space 3}  .322527
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0011652{col 29}{space 2} .0020847{col 40}{space 1}   -0.56{col 49}{space 3}0.576{col 57}{space 4}-.0052517{col 70}{space 3} .0029213
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1844313{col 29}{space 2} .0688023{col 40}{space 1}   -2.68{col 49}{space 3}0.007{col 57}{space 4}-.3193012{col 70}{space 3}-.0495614
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0396828{col 29}{space 2}   .03679{col 40}{space 1}    1.08{col 49}{space 3}0.281{col 57}{space 4}-.0324349{col 70}{space 3} .1118005
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0184806{col 29}{space 2} .0383291{col 40}{space 1}    0.48{col 49}{space 3}0.630{col 57}{space 4}-.0566541{col 70}{space 3} .0936153
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1705575{col 29}{space 2} .0380654{col 40}{space 1}    4.48{col 49}{space 3}0.000{col 57}{space 4} .0959397{col 70}{space 3} .2451753
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0939078{col 29}{space 2} .0444695{col 40}{space 1}    2.11{col 49}{space 3}0.035{col 57}{space 4} .0067364{col 70}{space 3} .1810793
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1826989{col 29}{space 2} .0479693{col 40}{space 1}    3.81{col 49}{space 3}0.000{col 57}{space 4} .0886669{col 70}{space 3} .2767309
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2513778{col 29}{space 2} .0389192{col 40}{space 1}    6.46{col 49}{space 3}0.000{col 57}{space 4} .1750864{col 70}{space 3} .3276693
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0252936{col 29}{space 2} .0588724{col 40}{space 1}    0.43{col 49}{space 3}0.667{col 57}{space 4}-.0901112{col 70}{space 3} .1406984
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0013153{col 29}{space 2} .0107079{col 40}{space 1}    0.12{col 49}{space 3}0.902{col 57}{space 4}-.0196749{col 70}{space 3} .0223055
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1346934{col 29}{space 2} .1000869{col 40}{space 1}    1.35{col 49}{space 3}0.178{col 57}{space 4}-.0615023{col 70}{space 3} .3308891
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.6732776{col 29}{space 2} .0479421{col 40}{space 1}  -14.04{col 49}{space 3}0.000{col 57}{space 4}-.7672563{col 70}{space 3}-.5792989
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.5760096{col 29}{space 2} .0468179{col 40}{space 1}  -12.30{col 49}{space 3}0.000{col 57}{space 4}-.6677845{col 70}{space 3}-.4842348
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.3786474{col 29}{space 2} .0453715{col 40}{space 1}   -8.35{col 49}{space 3}0.000{col 57}{space 4} -.467587{col 70}{space 3}-.2897078
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.733315{col 29}{space 2} .1366349{col 40}{space 1}   41.96{col 49}{space 3}0.000{col 57}{space 4} 5.465476{col 70}{space 3} 6.001154
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.5139972
        {txt}sigma_e {c |} {res} 1.2351846
            {txt}rho {c |} {res} .60038411{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  no_species   $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    21,117
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    10,363

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0385{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0551{col 63}{txt}avg{col 67}={col 69}{res}       2.0
{txt}     overall = {res}0.0559{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}17{txt},{res}10362{txt}){col 67}={col 70}{res}    24.82
{txt}corr(u_i, Xb){col 16}= {res}-0.0044{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2} .0622171{col 29}{space 2} .0058203{col 40}{space 1}   10.69{col 49}{space 3}0.000{col 57}{space 4} .0508082{col 70}{space 3} .0736261
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0287381{col 29}{space 2} .0085855{col 40}{space 1}    3.35{col 49}{space 3}0.001{col 57}{space 4} .0119088{col 70}{space 3} .0455674
{txt}dependent_share {c |}{col 17}{res}{space 2} .3300603{col 29}{space 2} .0843124{col 40}{space 1}    3.91{col 49}{space 3}0.000{col 57}{space 4} .1647917{col 70}{space 3} .4953289
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0114612{col 29}{space 2} .0024802{col 40}{space 1}   -4.62{col 49}{space 3}0.000{col 57}{space 4}-.0163228{col 70}{space 3}-.0065996
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0646082{col 29}{space 2} .0690718{col 40}{space 1}   -0.94{col 49}{space 3}0.350{col 57}{space 4}-.2000022{col 70}{space 3} .0707859
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}-.0082713{col 29}{space 2} .0519214{col 40}{space 1}   -0.16{col 49}{space 3}0.873{col 57}{space 4}-.1100472{col 70}{space 3} .0935047
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}  .176733{col 29}{space 2} .0591695{col 40}{space 1}    2.99{col 49}{space 3}0.003{col 57}{space 4} .0607494{col 70}{space 3} .2927166
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2796722{col 29}{space 2} .0397727{col 40}{space 1}    7.03{col 49}{space 3}0.000{col 57}{space 4}   .20171{col 70}{space 3} .3576344
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1199889{col 29}{space 2} .0428945{col 40}{space 1}    2.80{col 49}{space 3}0.005{col 57}{space 4} .0359075{col 70}{space 3} .2040704
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1049798{col 29}{space 2} .0300239{col 40}{space 1}    3.50{col 49}{space 3}0.000{col 57}{space 4} .0461271{col 70}{space 3} .1638325
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2386466{col 29}{space 2} .0314391{col 40}{space 1}    7.59{col 49}{space 3}0.000{col 57}{space 4}   .17702{col 70}{space 3} .3002733
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0307157{col 29}{space 2} .0343513{col 40}{space 1}   -0.89{col 49}{space 3}0.371{col 57}{space 4}-.0980508{col 70}{space 3} .0366194
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0108329{col 29}{space 2} .0036818{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} .0036158{col 70}{space 3} .0180499
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.1946397{col 29}{space 2} .0445449{col 40}{space 1}   -4.37{col 49}{space 3}0.000{col 57}{space 4}-.2819563{col 70}{space 3}-.1073232
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.1011908{col 29}{space 2} .0316086{col 40}{space 1}   -3.20{col 49}{space 3}0.001{col 57}{space 4}-.1631498{col 70}{space 3}-.0392318
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.0635467{col 29}{space 2} .0273073{col 40}{space 1}   -2.33{col 49}{space 3}0.020{col 57}{space 4}-.1170743{col 70}{space 3} -.010019
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1604009{col 29}{space 2} .0322765{col 40}{space 1}    4.97{col 49}{space 3}0.000{col 57}{space 4} .0971327{col 70}{space 3} .2236691
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.517622{col 29}{space 2} .1433952{col 40}{space 1}   38.48{col 49}{space 3}0.000{col 57}{space 4}  5.23654{col 70}{space 3} 5.798705
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3930622
        {txt}sigma_e {c |} {res} 1.2490973
            {txt}rho {c |} {res}  .5543263{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  no_species   $xlist   $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    20,313
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,107

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0478{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2170{col 63}{txt}avg{col 67}={col 69}{res}       4.0
{txt}     overall = {res}0.1419{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}19{txt},{res}5106{txt}){col 67}={col 70}{res}    36.23
{txt}corr(u_i, Xb){col 16}= {res}0.2117{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}no_species {c |}{col 17}{res}{space 2} .0468232{col 29}{space 2} .0056102{col 40}{space 1}    8.35{col 49}{space 3}0.000{col 57}{space 4} .0358247{col 70}{space 3} .0578217
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0132312{col 29}{space 2} .0079732{col 40}{space 1}    1.66{col 49}{space 3}0.097{col 57}{space 4}-.0023997{col 70}{space 3} .0288621
{txt}dependent_share {c |}{col 17}{res}{space 2} .1799379{col 29}{space 2} .0731549{col 40}{space 1}    2.46{col 49}{space 3}0.014{col 57}{space 4} .0365229{col 70}{space 3} .3233529
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0035078{col 29}{space 2}  .002455{col 40}{space 1}    1.43{col 49}{space 3}0.153{col 57}{space 4}-.0013051{col 70}{space 3} .0083207
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0424753{col 29}{space 2}  .057078{col 40}{space 1}    0.74{col 49}{space 3}0.457{col 57}{space 4}-.0694221{col 70}{space 3} .1543727
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1422716{col 29}{space 2} .0416703{col 40}{space 1}    3.41{col 49}{space 3}0.001{col 57}{space 4}   .06058{col 70}{space 3} .2239632
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2303988{col 29}{space 2} .0501052{col 40}{space 1}    4.60{col 49}{space 3}0.000{col 57}{space 4} .1321711{col 70}{space 3} .3286265
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2638545{col 29}{space 2}  .034105{col 40}{space 1}    7.74{col 49}{space 3}0.000{col 57}{space 4} .1969941{col 70}{space 3} .3307148
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .3476901{col 29}{space 2} .0347225{col 40}{space 1}   10.01{col 49}{space 3}0.000{col 57}{space 4}  .279619{col 70}{space 3} .4157611
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0657083{col 29}{space 2} .0278721{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4}  .011067{col 70}{space 3} .1203497
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .1921681{col 29}{space 2} .0285624{col 40}{space 1}    6.73{col 49}{space 3}0.000{col 57}{space 4} .1361737{col 70}{space 3} .2481626
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0300737{col 29}{space 2} .0258784{col 40}{space 1}    1.16{col 49}{space 3}0.245{col 57}{space 4} -.020659{col 70}{space 3} .0808065
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0004823{col 29}{space 2} .0012617{col 40}{space 1}    0.38{col 49}{space 3}0.702{col 57}{space 4}-.0019911{col 70}{space 3} .0029558
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  -.04297{col 29}{space 2} .0355084{col 40}{space 1}   -1.21{col 49}{space 3}0.226{col 57}{space 4}-.1125818{col 70}{space 3} .0266417
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1686166{col 29}{space 2} .0335513{col 40}{space 1}   -5.03{col 49}{space 3}0.000{col 57}{space 4}-.2343914{col 70}{space 3}-.1028417
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0372563{col 29}{space 2} .0319405{col 40}{space 1}   -1.17{col 49}{space 3}0.243{col 57}{space 4}-.0998734{col 70}{space 3} .0253608
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .3645146{col 29}{space 2} .0322328{col 40}{space 1}   11.31{col 49}{space 3}0.000{col 57}{space 4} .3013245{col 70}{space 3} .4277048
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0845987{col 29}{space 2} .0317354{col 40}{space 1}    2.67{col 49}{space 3}0.008{col 57}{space 4} .0223838{col 70}{space 3} .1468136
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2920198{col 29}{space 2} .0298864{col 40}{space 1}    9.77{col 49}{space 3}0.000{col 57}{space 4} .2334296{col 70}{space 3} .3506099
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.492577{col 29}{space 2} .1383167{col 40}{space 1}   32.48{col 49}{space 3}0.000{col 57}{space 4} 4.221417{col 70}{space 3} 4.763737
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2409542
        {txt}sigma_e {c |} {res} 1.2845376
            {txt}rho {c |} {res} .48274775{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  s20_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file s20_fe.rtf not found)
(output written to {browse  `"s20_fe.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                                   S21                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist     i.year, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    89,742
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    36,644

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0353{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0808{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.0653{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}24{txt},{res}36643{txt}){col 67}={col 70}{res}    73.96
{txt}corr(u_i, Xb){col 16}= {res}0.0750{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0991842{col 29}{space 2} .0052295{col 40}{space 1}   18.97{col 49}{space 3}0.000{col 57}{space 4} .0889342{col 70}{space 3} .1094343
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0229616{col 29}{space 2} .0042844{col 40}{space 1}    5.36{col 49}{space 3}0.000{col 57}{space 4}  .014564{col 70}{space 3} .0313591
{txt}dependent_share {c |}{col 17}{res}{space 2} .1000683{col 29}{space 2}  .037221{col 40}{space 1}    2.69{col 49}{space 3}0.007{col 57}{space 4}  .027114{col 70}{space 3} .1730227
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0037119{col 29}{space 2} .0011548{col 40}{space 1}   -3.21{col 49}{space 3}0.001{col 57}{space 4}-.0059753{col 70}{space 3}-.0014486
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0983047{col 29}{space 2}  .029965{col 40}{space 1}   -3.28{col 49}{space 3}0.001{col 57}{space 4} -.157037{col 70}{space 3}-.0395725
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0853208{col 29}{space 2} .0200768{col 40}{space 1}    4.25{col 49}{space 3}0.000{col 57}{space 4} .0459697{col 70}{space 3}  .124672
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1111341{col 29}{space 2} .0251728{col 40}{space 1}    4.41{col 49}{space 3}0.000{col 57}{space 4} .0617946{col 70}{space 3} .1604737
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1885969{col 29}{space 2} .0174305{col 40}{space 1}   10.82{col 49}{space 3}0.000{col 57}{space 4} .1544327{col 70}{space 3} .2227611
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1536839{col 29}{space 2} .0201602{col 40}{space 1}    7.62{col 49}{space 3}0.000{col 57}{space 4} .1141694{col 70}{space 3} .1931984
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1197162{col 29}{space 2} .0166316{col 40}{space 1}    7.20{col 49}{space 3}0.000{col 57}{space 4} .0871177{col 70}{space 3} .1523146
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2134656{col 29}{space 2} .0155718{col 40}{space 1}   13.71{col 49}{space 3}0.000{col 57}{space 4} .1829444{col 70}{space 3} .2439868
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0340832{col 29}{space 2} .0154979{col 40}{space 1}    2.20{col 49}{space 3}0.028{col 57}{space 4}  .003707{col 70}{space 3} .0644595
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0037318{col 29}{space 2} .0013022{col 40}{space 1}    2.87{col 49}{space 3}0.004{col 57}{space 4} .0011793{col 70}{space 3} .0062842
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0069365{col 29}{space 2} .0208914{col 40}{space 1}   -0.33{col 49}{space 3}0.740{col 57}{space 4}-.0478842{col 70}{space 3} .0340113
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1156228{col 29}{space 2} .0410177{col 40}{space 1}   -2.82{col 49}{space 3}0.005{col 57}{space 4}-.1960186{col 70}{space 3} -.035227
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .0685216{col 29}{space 2} .0289464{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0117857{col 70}{space 3} .1252574
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2559261{col 29}{space 2}  .035173{col 40}{space 1}    7.28{col 49}{space 3}0.000{col 57}{space 4}  .186986{col 70}{space 3} .3248663
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0965477{col 29}{space 2} .0298031{col 40}{space 1}    3.24{col 49}{space 3}0.001{col 57}{space 4} .0381327{col 70}{space 3} .1549626
{txt}{space 10}2013  {c |}{col 17}{res}{space 2}  .255196{col 29}{space 2} .0349818{col 40}{space 1}    7.30{col 49}{space 3}0.000{col 57}{space 4} .1866307{col 70}{space 3} .3237614
{txt}{space 10}2014  {c |}{col 17}{res}{space 2}  .237276{col 29}{space 2} .0392827{col 40}{space 1}    6.04{col 49}{space 3}0.000{col 57}{space 4} .1602809{col 70}{space 3} .3142712
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3335132{col 29}{space 2} .0335927{col 40}{space 1}    9.93{col 49}{space 3}0.000{col 57}{space 4} .2676706{col 70}{space 3} .3993558
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0063109{col 29}{space 2}  .046574{col 40}{space 1}   -0.14{col 49}{space 3}0.892{col 57}{space 4}-.0975973{col 70}{space 3} .0849755
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .5583109{col 29}{space 2} .0392768{col 40}{space 1}   14.21{col 49}{space 3}0.000{col 57}{space 4} .4813273{col 70}{space 3} .6352946
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .2578429{col 29}{space 2} .0382238{col 40}{space 1}    6.75{col 49}{space 3}0.000{col 57}{space 4} .1829231{col 70}{space 3} .3327628
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.833411{col 29}{space 2} .0659193{col 40}{space 1}   73.32{col 49}{space 3}0.000{col 57}{space 4} 4.704208{col 70}{space 3} 4.962615
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4869992
        {txt}sigma_e {c |} {res} 1.2548029
            {txt}rho {c |} {res} .58408439{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    13,511
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,436

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0317{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0499{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0520{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}15{txt},{res}5435{txt}){col 67}={col 70}{res}    17.37
{txt}corr(u_i, Xb){col 16}= {res}0.0251{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0580927{col 29}{space 2} .0107719{col 40}{space 1}    5.39{col 49}{space 3}0.000{col 57}{space 4} .0369756{col 70}{space 3} .0792099
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0594312{col 29}{space 2} .0125885{col 40}{space 1}    4.72{col 49}{space 3}0.000{col 57}{space 4} .0347527{col 70}{space 3} .0841098
{txt}dependent_share {c |}{col 17}{res}{space 2}-.1209797{col 29}{space 2} .0907804{col 40}{space 1}   -1.33{col 49}{space 3}0.183{col 57}{space 4}-.2989457{col 70}{space 3} .0569862
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0091156{col 29}{space 2} .0027335{col 40}{space 1}    3.33{col 49}{space 3}0.001{col 57}{space 4} .0037568{col 70}{space 3} .0144744
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0328538{col 29}{space 2} .0782104{col 40}{space 1}   -0.42{col 49}{space 3}0.674{col 57}{space 4}-.1861775{col 70}{space 3} .1204698
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1885164{col 29}{space 2} .0454131{col 40}{space 1}    4.15{col 49}{space 3}0.000{col 57}{space 4} .0994885{col 70}{space 3} .2775443
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1272575{col 29}{space 2} .1314193{col 40}{space 1}   -0.97{col 49}{space 3}0.333{col 57}{space 4}-.3848919{col 70}{space 3} .1303769
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1842887{col 29}{space 2} .0369577{col 40}{space 1}    4.99{col 49}{space 3}0.000{col 57}{space 4} .1118369{col 70}{space 3} .2567406
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1081754{col 29}{space 2}  .044892{col 40}{space 1}    2.41{col 49}{space 3}0.016{col 57}{space 4} .0201692{col 70}{space 3} .1961817
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0311966{col 29}{space 2} .0535828{col 40}{space 1}   -0.58{col 49}{space 3}0.560{col 57}{space 4}-.1362402{col 70}{space 3} .0738471
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2166147{col 29}{space 2} .0471147{col 40}{space 1}    4.60{col 49}{space 3}0.000{col 57}{space 4} .1242509{col 70}{space 3} .3089785
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0093837{col 29}{space 2} .0355612{col 40}{space 1}   -0.26{col 49}{space 3}0.792{col 57}{space 4}-.0790979{col 70}{space 3} .0603306
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0106041{col 29}{space 2} .0044345{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4} .0019106{col 70}{space 3} .0192976
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0158939{col 29}{space 2}   .04554{col 40}{space 1}    0.35{col 49}{space 3}0.727{col 57}{space 4}-.0733829{col 70}{space 3} .1051706
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.1975316{col 29}{space 2} .0216776{col 40}{space 1}   -9.11{col 49}{space 3}0.000{col 57}{space 4}-.2400283{col 70}{space 3}-.1550349
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  3.40638{col 29}{space 2} .1418449{col 40}{space 1}   24.01{col 49}{space 3}0.000{col 57}{space 4} 3.128307{col 70}{space 3} 3.684453
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3234319
        {txt}sigma_e {c |} {res} 1.1126502
            {txt}rho {c |} {res} .58588189{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   $year_MALAWI if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     9,163
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,447

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0427{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2809{col 63}{txt}avg{col 67}={col 69}{res}       2.7
{txt}     overall = {res}0.2141{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}16{txt},{res}3446{txt}){col 67}={col 70}{res}    15.16
{txt}corr(u_i, Xb){col 16}= {res}0.3221{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1099189{col 29}{space 2} .0146761{col 40}{space 1}    7.49{col 49}{space 3}0.000{col 57}{space 4} .0811442{col 70}{space 3} .1386937
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0121287{col 29}{space 2} .0137837{col 40}{space 1}    0.88{col 49}{space 3}0.379{col 57}{space 4}-.0148964{col 70}{space 3} .0391539
{txt}dependent_share {c |}{col 17}{res}{space 2}-.3200352{col 29}{space 2} .0997939{col 40}{space 1}   -3.21{col 49}{space 3}0.001{col 57}{space 4}-.5156963{col 70}{space 3}-.1243741
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0011718{col 29}{space 2} .0031053{col 40}{space 1}   -0.38{col 49}{space 3}0.706{col 57}{space 4}-.0072601{col 70}{space 3} .0049165
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1197731{col 29}{space 2} .0673107{col 40}{space 1}   -1.78{col 49}{space 3}0.075{col 57}{space 4} -.251746{col 70}{space 3} .0121997
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1481664{col 29}{space 2} .0618242{col 40}{space 1}    2.40{col 49}{space 3}0.017{col 57}{space 4} .0269506{col 70}{space 3} .2693821
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2468851{col 29}{space 2} .1355384{col 40}{space 1}    1.82{col 49}{space 3}0.069{col 57}{space 4}-.0188586{col 70}{space 3} .5126287
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2609881{col 29}{space 2}  .052892{col 40}{space 1}    4.93{col 49}{space 3}0.000{col 57}{space 4} .1572853{col 70}{space 3}  .364691
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .4576289{col 29}{space 2} .0858206{col 40}{space 1}    5.33{col 49}{space 3}0.000{col 57}{space 4} .2893646{col 70}{space 3} .6258932
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1720238{col 29}{space 2} .0563217{col 40}{space 1}    3.05{col 49}{space 3}0.002{col 57}{space 4} .0615965{col 70}{space 3}  .282451
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2596507{col 29}{space 2} .0415551{col 40}{space 1}    6.25{col 49}{space 3}0.000{col 57}{space 4} .1781755{col 70}{space 3} .3411259
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1188835{col 29}{space 2} .0389603{col 40}{space 1}   -3.05{col 49}{space 3}0.002{col 57}{space 4}-.1952712{col 70}{space 3}-.0424959
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .025253{col 29}{space 2} .0367274{col 40}{space 1}    0.69{col 49}{space 3}0.492{col 57}{space 4}-.0467566{col 70}{space 3} .0972626
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1222604{col 29}{space 2} .0602657{col 40}{space 1}    2.03{col 49}{space 3}0.043{col 57}{space 4} .0041003{col 70}{space 3} .2404205
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .1536879{col 29}{space 2} .0496689{col 40}{space 1}    3.09{col 49}{space 3}0.002{col 57}{space 4} .0563045{col 70}{space 3} .2510714
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .0972789{col 29}{space 2} .0388761{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0210564{col 70}{space 3} .1735014
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.614342{col 29}{space 2} .1678381{col 40}{space 1}   33.45{col 49}{space 3}0.000{col 57}{space 4}  5.28527{col 70}{space 3} 5.943414
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3195811
        {txt}sigma_e {c |} {res} 1.3063515
            {txt}rho {c |} {res} .50503793{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     7,046
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,069

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0491{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0017{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0087{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}15{txt},{res}4068{txt}){col 67}={col 70}{res}     9.28
{txt}corr(u_i, Xb){col 16}= {res}-0.1616{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2515074{col 29}{space 2} .0349225{col 40}{space 1}    7.20{col 49}{space 3}0.000{col 57}{space 4} .1830401{col 70}{space 3} .3199747
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0479817{col 29}{space 2}  .017368{col 40}{space 1}   -2.76{col 49}{space 3}0.006{col 57}{space 4}-.0820325{col 70}{space 3} -.013931
{txt}dependent_share {c |}{col 17}{res}{space 2}  .153699{col 29}{space 2}  .222244{col 40}{space 1}    0.69{col 49}{space 3}0.489{col 57}{space 4}-.2820208{col 70}{space 3} .5894188
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0062399{col 29}{space 2} .0054483{col 40}{space 1}    1.15{col 49}{space 3}0.252{col 57}{space 4}-.0044418{col 70}{space 3} .0169215
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .2701388{col 29}{space 2} .1499618{col 40}{space 1}    1.80{col 49}{space 3}0.072{col 57}{space 4}-.0238685{col 70}{space 3} .5641461
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1937386{col 29}{space 2} .0826613{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 57}{space 4} .0316772{col 70}{space 3}    .3558
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2680218{col 29}{space 2} .0957728{col 40}{space 1}    2.80{col 49}{space 3}0.005{col 57}{space 4} .0802548{col 70}{space 3} .4557888
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1299428{col 29}{space 2} .0742712{col 40}{space 1}    1.75{col 49}{space 3}0.080{col 57}{space 4}-.0156694{col 70}{space 3}  .275555
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2485314{col 29}{space 2} .1047557{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0431528{col 70}{space 3}   .45391
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2286475{col 29}{space 2} .0835462{col 40}{space 1}    2.74{col 49}{space 3}0.006{col 57}{space 4} .0648512{col 70}{space 3} .3924438
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1656644{col 29}{space 2} .0652183{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4} -.293528{col 70}{space 3}-.0378009
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0230835{col 29}{space 2} .0658384{col 40}{space 1}    0.35{col 49}{space 3}0.726{col 57}{space 4}-.1059957{col 70}{space 3} .1521627
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0055231{col 29}{space 2} .0026183{col 40}{space 1}    2.11{col 49}{space 3}0.035{col 57}{space 4} .0003899{col 70}{space 3} .0106563
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1066655{col 29}{space 2} .3453379{col 40}{space 1}    0.31{col 49}{space 3}0.757{col 57}{space 4}-.5703857{col 70}{space 3} .7837168
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .3148842{col 29}{space 2}  .041622{col 40}{space 1}    7.57{col 49}{space 3}0.000{col 57}{space 4} .2332823{col 70}{space 3} .3964861
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.727645{col 29}{space 2} .3102111{col 40}{space 1}   15.24{col 49}{space 3}0.000{col 57}{space 4} 4.119461{col 70}{space 3} 5.335828
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.462521
        {txt}sigma_e {c |} {res} 1.3703359
            {txt}rho {c |} {res} .53250698{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    18,592
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,222

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0472{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0612{col 63}{txt}avg{col 67}={col 69}{res}       2.3
{txt}     overall = {res}0.0521{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}8221{txt}){col 67}={col 70}{res}    27.33
{txt}corr(u_i, Xb){col 16}= {res}0.0110{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}  .085869{col 29}{space 2} .0143566{col 40}{space 1}    5.98{col 49}{space 3}0.000{col 57}{space 4} .0577264{col 70}{space 3} .1140116
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0236367{col 29}{space 2} .0090079{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4}  .005979{col 70}{space 3} .0412944
{txt}dependent_share {c |}{col 17}{res}{space 2} .1664305{col 29}{space 2} .0778669{col 40}{space 1}    2.14{col 49}{space 3}0.033{col 57}{space 4} .0137917{col 70}{space 3} .3190694
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} -.001128{col 29}{space 2} .0020851{col 40}{space 1}   -0.54{col 49}{space 3}0.589{col 57}{space 4}-.0052153{col 70}{space 3} .0029593
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1806987{col 29}{space 2} .0689811{col 40}{space 1}   -2.62{col 49}{space 3}0.009{col 57}{space 4}-.3159191{col 70}{space 3}-.0454782
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0371736{col 29}{space 2} .0367619{col 40}{space 1}    1.01{col 49}{space 3}0.312{col 57}{space 4}-.0348891{col 70}{space 3} .1092362
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0211419{col 29}{space 2} .0382974{col 40}{space 1}    0.55{col 49}{space 3}0.581{col 57}{space 4}-.0539307{col 70}{space 3} .0962145
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1699234{col 29}{space 2} .0381137{col 40}{space 1}    4.46{col 49}{space 3}0.000{col 57}{space 4} .0952109{col 70}{space 3} .2446359
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0934645{col 29}{space 2} .0445019{col 40}{space 1}    2.10{col 49}{space 3}0.036{col 57}{space 4} .0062294{col 70}{space 3} .1806995
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1845602{col 29}{space 2} .0479464{col 40}{space 1}    3.85{col 49}{space 3}0.000{col 57}{space 4} .0905732{col 70}{space 3} .2785472
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2517996{col 29}{space 2} .0387963{col 40}{space 1}    6.49{col 49}{space 3}0.000{col 57}{space 4} .1757491{col 70}{space 3} .3278501
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0262992{col 29}{space 2} .0587217{col 40}{space 1}    0.45{col 49}{space 3}0.654{col 57}{space 4}-.0888102{col 70}{space 3} .1414086
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0015747{col 29}{space 2} .0106855{col 40}{space 1}    0.15{col 49}{space 3}0.883{col 57}{space 4}-.0193716{col 70}{space 3}  .022521
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1911117{col 29}{space 2} .0994429{col 40}{space 1}    1.92{col 49}{space 3}0.055{col 57}{space 4}-.0038215{col 70}{space 3} .3860448
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.6553141{col 29}{space 2} .0480026{col 40}{space 1}  -13.65{col 49}{space 3}0.000{col 57}{space 4}-.7494114{col 70}{space 3}-.5612169
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.5563072{col 29}{space 2} .0469014{col 40}{space 1}  -11.86{col 49}{space 3}0.000{col 57}{space 4}-.6482458{col 70}{space 3}-.4643685
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} -.359112{col 29}{space 2} .0455686{col 40}{space 1}   -7.88{col 49}{space 3}0.000{col 57}{space 4} -.448438{col 70}{space 3}-.2697861
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.697853{col 29}{space 2} .1371964{col 40}{space 1}   41.53{col 49}{space 3}0.000{col 57}{space 4} 5.428914{col 70}{space 3} 5.966793
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.5077277
        {txt}sigma_e {c |} {res} 1.2348383
            {txt}rho {c |} {res} .59852603{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    21,117
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    10,363

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0450{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0324{col 63}{txt}avg{col 67}={col 69}{res}       2.0
{txt}     overall = {res}0.0371{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}17{txt},{res}10362{txt}){col 67}={col 70}{res}    28.41
{txt}corr(u_i, Xb){col 16}= {res}-0.0803{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1467958{col 29}{space 2}  .010885{col 40}{space 1}   13.49{col 49}{space 3}0.000{col 57}{space 4} .1254591{col 70}{space 3} .1681325
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0267751{col 29}{space 2} .0085266{col 40}{space 1}    3.14{col 49}{space 3}0.002{col 57}{space 4} .0100613{col 70}{space 3}  .043489
{txt}dependent_share {c |}{col 17}{res}{space 2} .3148641{col 29}{space 2} .0840218{col 40}{space 1}    3.75{col 49}{space 3}0.000{col 57}{space 4}  .150165{col 70}{space 3} .4795631
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0121244{col 29}{space 2} .0024552{col 40}{space 1}   -4.94{col 49}{space 3}0.000{col 57}{space 4}-.0169371{col 70}{space 3}-.0073117
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} -.057124{col 29}{space 2} .0686624{col 40}{space 1}   -0.83{col 49}{space 3}0.405{col 57}{space 4}-.1917157{col 70}{space 3} .0774676
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}-.0026643{col 29}{space 2} .0517453{col 40}{space 1}   -0.05{col 49}{space 3}0.959{col 57}{space 4}-.1040951{col 70}{space 3} .0987665
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1641187{col 29}{space 2}  .058938{col 40}{space 1}    2.78{col 49}{space 3}0.005{col 57}{space 4} .0485888{col 70}{space 3} .2796487
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2750367{col 29}{space 2} .0396892{col 40}{space 1}    6.93{col 49}{space 3}0.000{col 57}{space 4} .1972381{col 70}{space 3} .3528352
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1173101{col 29}{space 2} .0428181{col 40}{space 1}    2.74{col 49}{space 3}0.006{col 57}{space 4} .0333784{col 70}{space 3} .2012417
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1032044{col 29}{space 2} .0298835{col 40}{space 1}    3.45{col 49}{space 3}0.001{col 57}{space 4}  .044627{col 70}{space 3} .1617818
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2376948{col 29}{space 2} .0313646{col 40}{space 1}    7.58{col 49}{space 3}0.000{col 57}{space 4} .1762143{col 70}{space 3} .2991754
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0345959{col 29}{space 2} .0342345{col 40}{space 1}   -1.01{col 49}{space 3}0.312{col 57}{space 4}-.1017021{col 70}{space 3} .0325102
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0101195{col 29}{space 2} .0035692{col 40}{space 1}    2.84{col 49}{space 3}0.005{col 57}{space 4} .0031231{col 70}{space 3} .0171159
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.1113718{col 29}{space 2} .0412977{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4}-.1923233{col 70}{space 3}-.0304202
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2} -.124727{col 29}{space 2} .0316787{col 40}{space 1}   -3.94{col 49}{space 3}0.000{col 57}{space 4}-.1868234{col 70}{space 3}-.0626307
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2} -.062013{col 29}{space 2} .0272529{col 40}{space 1}   -2.28{col 49}{space 3}0.023{col 57}{space 4}-.1154339{col 70}{space 3}-.0085921
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1541549{col 29}{space 2}  .032075{col 40}{space 1}    4.81{col 49}{space 3}0.000{col 57}{space 4} .0912818{col 70}{space 3} .2170281
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.442704{col 29}{space 2} .1426093{col 40}{space 1}   38.17{col 49}{space 3}0.000{col 57}{space 4} 5.163162{col 70}{space 3} 5.722245
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4146714
        {txt}sigma_e {c |} {res} 1.2448832
            {txt}rho {c |} {res} .56358167{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist    $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    20,313
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,107

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0493{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2107{col 63}{txt}avg{col 67}={col 69}{res}       4.0
{txt}     overall = {res}0.1392{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}19{txt},{res}5106{txt}){col 67}={col 70}{res}    37.47
{txt}corr(u_i, Xb){col 16}= {res}0.2032{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0956478{col 29}{space 2} .0100723{col 40}{space 1}    9.50{col 49}{space 3}0.000{col 57}{space 4} .0759017{col 70}{space 3} .1153939
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0141363{col 29}{space 2} .0079449{col 40}{space 1}    1.78{col 49}{space 3}0.075{col 57}{space 4}-.0014391{col 70}{space 3} .0297117
{txt}dependent_share {c |}{col 17}{res}{space 2}  .172383{col 29}{space 2} .0731022{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0290714{col 70}{space 3} .3156946
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0027644{col 29}{space 2}  .002453{col 40}{space 1}    1.13{col 49}{space 3}0.260{col 57}{space 4}-.0020445{col 70}{space 3} .0075732
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0413829{col 29}{space 2} .0567468{col 40}{space 1}    0.73{col 49}{space 3}0.466{col 57}{space 4}-.0698652{col 70}{space 3}  .152631
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1374824{col 29}{space 2} .0415387{col 40}{space 1}    3.31{col 49}{space 3}0.001{col 57}{space 4} .0560487{col 70}{space 3}  .218916
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2301488{col 29}{space 2} .0499805{col 40}{space 1}    4.60{col 49}{space 3}0.000{col 57}{space 4} .1321656{col 70}{space 3}  .328132
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2600991{col 29}{space 2} .0340633{col 40}{space 1}    7.64{col 49}{space 3}0.000{col 57}{space 4} .1933205{col 70}{space 3} .3268777
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .3330836{col 29}{space 2}  .034582{col 40}{space 1}    9.63{col 49}{space 3}0.000{col 57}{space 4} .2652881{col 70}{space 3}  .400879
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0666801{col 29}{space 2} .0278695{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4}  .012044{col 70}{space 3} .1213162
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .1961253{col 29}{space 2} .0285438{col 40}{space 1}    6.87{col 49}{space 3}0.000{col 57}{space 4} .1401673{col 70}{space 3} .2520834
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0307233{col 29}{space 2} .0258307{col 40}{space 1}    1.19{col 49}{space 3}0.234{col 57}{space 4}-.0199161{col 70}{space 3} .0813626
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0005216{col 29}{space 2} .0012456{col 40}{space 1}    0.42{col 49}{space 3}0.675{col 57}{space 4}-.0019204{col 70}{space 3} .0029636
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0041431{col 29}{space 2} .0337864{col 40}{space 1}    0.12{col 49}{space 3}0.902{col 57}{space 4}-.0620927{col 70}{space 3}  .070379
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1529158{col 29}{space 2} .0335529{col 40}{space 1}   -4.56{col 49}{space 3}0.000{col 57}{space 4}-.2186939{col 70}{space 3}-.0871378
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0429543{col 29}{space 2} .0319724{col 40}{space 1}   -1.34{col 49}{space 3}0.179{col 57}{space 4}-.1056338{col 70}{space 3} .0197252
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .3392777{col 29}{space 2}  .032216{col 40}{space 1}   10.53{col 49}{space 3}0.000{col 57}{space 4} .2761205{col 70}{space 3} .4024349
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0708465{col 29}{space 2}  .031678{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} .0087442{col 70}{space 3} .1329489
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2753943{col 29}{space 2} .0297683{col 40}{space 1}    9.25{col 49}{space 3}0.000{col 57}{space 4} .2170356{col 70}{space 3} .3337529
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.478174{col 29}{space 2} .1381529{col 40}{space 1}   32.41{col 49}{space 3}0.000{col 57}{space 4} 4.207335{col 70}{space 3} 4.749013
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2431224
        {txt}sigma_e {c |} {res} 1.2834766
            {txt}rho {c |} {res} .48403231{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  s21_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file s21_fe.rtf not found)
(output written to {browse  `"s21_fe.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S22                                        *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(7,192 observations deleted)

{com}. 
. eststo clear
{txt}
{com}. xtreg hdd9_own  pdd9   $xlist    i.year  , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    82,550
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    34,744

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0800{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.5010{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.4051{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}24{txt},{res}34743{txt}){col 67}={col 70}{res}   128.68
{txt}corr(u_i, Xb){col 16}= {res}0.4614{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2322595{col 29}{space 2} .0053487{col 40}{space 1}   43.42{col 49}{space 3}0.000{col 57}{space 4} .2217759{col 70}{space 3}  .242743
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0297421{col 29}{space 2} .0039705{col 40}{space 1}    7.49{col 49}{space 3}0.000{col 57}{space 4} .0219599{col 70}{space 3} .0375244
{txt}dependent_share {c |}{col 17}{res}{space 2}-.0154414{col 29}{space 2} .0325826{col 40}{space 1}   -0.47{col 49}{space 3}0.636{col 57}{space 4}-.0793043{col 70}{space 3} .0484215
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}  .002673{col 29}{space 2} .0009973{col 40}{space 1}    2.68{col 49}{space 3}0.007{col 57}{space 4} .0007183{col 70}{space 3} .0046277
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0655528{col 29}{space 2} .0261912{col 40}{space 1}   -2.50{col 49}{space 3}0.012{col 57}{space 4}-.1168883{col 70}{space 3}-.0142172
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0602797{col 29}{space 2} .0172216{col 40}{space 1}    3.50{col 49}{space 3}0.000{col 57}{space 4} .0265249{col 70}{space 3} .0940346
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0031245{col 29}{space 2} .0202519{col 40}{space 1}    0.15{col 49}{space 3}0.877{col 57}{space 4}-.0365698{col 70}{space 3} .0428188
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .0317132{col 29}{space 2} .0149002{col 40}{space 1}    2.13{col 49}{space 3}0.033{col 57}{space 4} .0025083{col 70}{space 3}  .060918
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.0096047{col 29}{space 2} .0177403{col 40}{space 1}   -0.54{col 49}{space 3}0.588{col 57}{space 4}-.0443762{col 70}{space 3} .0251668
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0742589{col 29}{space 2} .0141423{col 40}{space 1}   -5.25{col 49}{space 3}0.000{col 57}{space 4}-.1019783{col 70}{space 3}-.0465396
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .0025389{col 29}{space 2} .0139874{col 40}{space 1}    0.18{col 49}{space 3}0.856{col 57}{space 4}-.0248769{col 70}{space 3} .0299546
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} -.029671{col 29}{space 2} .0145807{col 40}{space 1}   -2.03{col 49}{space 3}0.042{col 57}{space 4}-.0582496{col 70}{space 3}-.0010924
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0041643{col 29}{space 2} .0013514{col 40}{space 1}    3.08{col 49}{space 3}0.002{col 57}{space 4} .0015155{col 70}{space 3} .0068132
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  .060396{col 29}{space 2} .0208052{col 40}{space 1}    2.90{col 49}{space 3}0.004{col 57}{space 4} .0196171{col 70}{space 3} .1011749
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.2316915{col 29}{space 2} .0353188{col 40}{space 1}   -6.56{col 49}{space 3}0.000{col 57}{space 4}-.3009176{col 70}{space 3}-.1624654
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} -.113537{col 29}{space 2} .0242464{col 40}{space 1}   -4.68{col 49}{space 3}0.000{col 57}{space 4}-.1610608{col 70}{space 3}-.0660132
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .1011354{col 29}{space 2} .0301008{col 40}{space 1}    3.36{col 49}{space 3}0.001{col 57}{space 4} .0421369{col 70}{space 3} .1601339
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-.0394486{col 29}{space 2} .0246859{col 40}{space 1}   -1.60{col 49}{space 3}0.110{col 57}{space 4}-.0878337{col 70}{space 3} .0089366
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .0073409{col 29}{space 2} .0297543{col 40}{space 1}    0.25{col 49}{space 3}0.805{col 57}{space 4}-.0509786{col 70}{space 3} .0656603
{txt}{space 10}2014  {c |}{col 17}{res}{space 2}-.2582815{col 29}{space 2} .0332442{col 40}{space 1}   -7.77{col 49}{space 3}0.000{col 57}{space 4}-.3234412{col 70}{space 3}-.1931217
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .0000571{col 29}{space 2} .0276101{col 40}{space 1}    0.00{col 49}{space 3}0.998{col 57}{space 4}-.0540595{col 70}{space 3} .0541737
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.4168476{col 29}{space 2} .0382882{col 40}{space 1}  -10.89{col 49}{space 3}0.000{col 57}{space 4}-.4918937{col 70}{space 3}-.3418015
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .1894434{col 29}{space 2} .0335086{col 40}{space 1}    5.65{col 49}{space 3}0.000{col 57}{space 4} .1237653{col 70}{space 3} .2551214
{txt}{space 10}2019  {c |}{col 17}{res}{space 2}-.2190059{col 29}{space 2} .0330354{col 40}{space 1}   -6.63{col 49}{space 3}0.000{col 57}{space 4}-.2837563{col 70}{space 3}-.1542555
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .8439738{col 29}{space 2} .0573277{col 40}{space 1}   14.72{col 49}{space 3}0.000{col 57}{space 4} .7316096{col 70}{space 3}  .956338
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.1161168
        {txt}sigma_e {c |} {res} 1.0171168
            {txt}rho {c |} {res} .54630867{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    10,583
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,088

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0295{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.5271{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.4048{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}15{txt},{res}5087{txt}){col 67}={col 70}{res}    10.03
{txt}corr(u_i, Xb){col 16}= {res}0.5511{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0709947{col 29}{space 2}  .011152{col 40}{space 1}    6.37{col 49}{space 3}0.000{col 57}{space 4}  .049132{col 70}{space 3} .0928573
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0423155{col 29}{space 2} .0123427{col 40}{space 1}    3.43{col 49}{space 3}0.001{col 57}{space 4} .0181184{col 70}{space 3} .0665125
{txt}dependent_share {c |}{col 17}{res}{space 2} -.050768{col 29}{space 2} .0801219{col 40}{space 1}   -0.63{col 49}{space 3}0.526{col 57}{space 4}-.2078414{col 70}{space 3} .1063054
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0043037{col 29}{space 2} .0023169{col 40}{space 1}    1.86{col 49}{space 3}0.063{col 57}{space 4}-.0002385{col 70}{space 3} .0088459
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0572864{col 29}{space 2} .0613823{col 40}{space 1}   -0.93{col 49}{space 3}0.351{col 57}{space 4}-.1776221{col 70}{space 3} .0630494
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}  .049859{col 29}{space 2} .0425581{col 40}{space 1}    1.17{col 49}{space 3}0.241{col 57}{space 4}-.0335733{col 70}{space 3} .1332912
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1450579{col 29}{space 2} .1231917{col 40}{space 1}   -1.18{col 49}{space 3}0.239{col 57}{space 4}-.3865666{col 70}{space 3} .0964507
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .017223{col 29}{space 2} .0354723{col 40}{space 1}    0.49{col 49}{space 3}0.627{col 57}{space 4}-.0523179{col 70}{space 3} .0867639
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.1416858{col 29}{space 2} .0409141{col 40}{space 1}   -3.46{col 49}{space 3}0.001{col 57}{space 4}-.2218949{col 70}{space 3}-.0614766
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0181411{col 29}{space 2} .0339754{col 40}{space 1}   -0.53{col 49}{space 3}0.593{col 57}{space 4}-.0847476{col 70}{space 3} .0484654
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.0218865{col 29}{space 2} .0406104{col 40}{space 1}   -0.54{col 49}{space 3}0.590{col 57}{space 4}-.1015003{col 70}{space 3} .0577273
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.2125349{col 29}{space 2}  .033463{col 40}{space 1}   -6.35{col 49}{space 3}0.000{col 57}{space 4}-.2781367{col 70}{space 3}-.1469331
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0131278{col 29}{space 2} .0080207{col 40}{space 1}    1.64{col 49}{space 3}0.102{col 57}{space 4}-.0025963{col 70}{space 3} .0288519
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0126907{col 29}{space 2} .0434651{col 40}{space 1}   -0.29{col 49}{space 3}0.770{col 57}{space 4} -.097901{col 70}{space 3} .0725196
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} -.115635{col 29}{space 2}  .017761{col 40}{space 1}   -6.51{col 49}{space 3}0.000{col 57}{space 4}-.1504542{col 70}{space 3}-.0808157
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .9324758{col 29}{space 2} .1259504{col 40}{space 1}    7.40{col 49}{space 3}0.000{col 57}{space 4} .6855589{col 70}{space 3} 1.179393
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.0493419
        {txt}sigma_e {c |} {res} .80682908
            {txt}rho {c |} {res}  .6284594{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist   $year_MALAWI if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     9,155
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,447

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.1674{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.5323{col 63}{txt}avg{col 67}={col 69}{res}       2.7
{txt}     overall = {res}0.4131{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}16{txt},{res}3446{txt}){col 67}={col 70}{res}    61.25
{txt}corr(u_i, Xb){col 16}= {res}0.3330{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .3135589{col 29}{space 2} .0137481{col 40}{space 1}   22.81{col 49}{space 3}0.000{col 57}{space 4} .2866036{col 70}{space 3} .3405142
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}  .015983{col 29}{space 2} .0121124{col 40}{space 1}    1.32{col 49}{space 3}0.187{col 57}{space 4}-.0077652{col 70}{space 3} .0397313
{txt}dependent_share {c |}{col 17}{res}{space 2}-.0021653{col 29}{space 2} .0852943{col 40}{space 1}   -0.03{col 49}{space 3}0.980{col 57}{space 4}-.1693978{col 70}{space 3} .1650672
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}  .005576{col 29}{space 2} .0027468{col 40}{space 1}    2.03{col 49}{space 3}0.042{col 57}{space 4} .0001903{col 70}{space 3} .0109616
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} -.107355{col 29}{space 2}  .057867{col 40}{space 1}   -1.86{col 49}{space 3}0.064{col 57}{space 4}-.2208121{col 70}{space 3} .0061021
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0287365{col 29}{space 2} .0505054{col 40}{space 1}    0.57{col 49}{space 3}0.569{col 57}{space 4} -.070287{col 70}{space 3}   .12776
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2239484{col 29}{space 2} .1256278{col 40}{space 1}    1.78{col 49}{space 3}0.075{col 57}{space 4} -.022364{col 70}{space 3} .4702608
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .0094231{col 29}{space 2} .0421526{col 40}{space 1}    0.22{col 49}{space 3}0.823{col 57}{space 4}-.0732235{col 70}{space 3} .0920698
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.0603237{col 29}{space 2} .0636716{col 40}{space 1}   -0.95{col 49}{space 3}0.343{col 57}{space 4}-.1851617{col 70}{space 3} .0645142
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0925645{col 29}{space 2} .0453876{col 40}{space 1}   -2.04{col 49}{space 3}0.041{col 57}{space 4}-.1815538{col 70}{space 3}-.0035751
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .0492469{col 29}{space 2}  .037127{col 40}{space 1}    1.33{col 49}{space 3}0.185{col 57}{space 4}-.0235461{col 70}{space 3}   .12204
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1292714{col 29}{space 2} .0331221{col 40}{space 1}   -3.90{col 49}{space 3}0.000{col 57}{space 4}-.1942124{col 70}{space 3}-.0643304
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .1555222{col 29}{space 2} .0415947{col 40}{space 1}    3.74{col 49}{space 3}0.000{col 57}{space 4} .0739694{col 70}{space 3}  .237075
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  .164801{col 29}{space 2} .0539329{col 40}{space 1}    3.06{col 49}{space 3}0.002{col 57}{space 4} .0590573{col 70}{space 3} .2705448
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .5957724{col 29}{space 2} .0425804{col 40}{space 1}   13.99{col 49}{space 3}0.000{col 57}{space 4}  .512287{col 70}{space 3} .6792578
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .2968661{col 29}{space 2} .0322904{col 40}{space 1}    9.19{col 49}{space 3}0.000{col 57}{space 4} .2335559{col 70}{space 3} .3601763
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .4046615{col 29}{space 2} .1486761{col 40}{space 1}    2.72{col 49}{space 3}0.007{col 57}{space 4} .1131594{col 70}{space 3} .6961636
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} .95753702
        {txt}sigma_e {c |} {res} 1.0803198
            {txt}rho {c |} {res} .43996698{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_own  pdd9   $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     7,044
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,069

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.1611{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.3187{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.2754{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}15{txt},{res}4068{txt}){col 67}={col 70}{res}    35.16
{txt}corr(u_i, Xb){col 16}= {res}0.2641{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1973433{col 29}{space 2} .0220894{col 40}{space 1}    8.93{col 49}{space 3}0.000{col 57}{space 4}  .154036{col 70}{space 3} .2406505
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0171728{col 29}{space 2} .0103188{col 40}{space 1}   -1.66{col 49}{space 3}0.096{col 57}{space 4}-.0374033{col 70}{space 3} .0030577
{txt}dependent_share {c |}{col 17}{res}{space 2} .0525524{col 29}{space 2} .1181595{col 40}{space 1}    0.44{col 49}{space 3}0.657{col 57}{space 4}-.1791049{col 70}{space 3} .2842098
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}  -.00189{col 29}{space 2} .0028848{col 40}{space 1}   -0.66{col 49}{space 3}0.512{col 57}{space 4}-.0075458{col 70}{space 3} .0037658
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1509048{col 29}{space 2} .0732159{col 40}{space 1}   -2.06{col 49}{space 3}0.039{col 57}{space 4}-.2944479{col 70}{space 3}-.0073617
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0852449{col 29}{space 2} .0473259{col 40}{space 1}    1.80{col 49}{space 3}0.072{col 57}{space 4}-.0075398{col 70}{space 3} .1780296
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0465643{col 29}{space 2} .0435759{col 40}{space 1}    1.07{col 49}{space 3}0.285{col 57}{space 4}-.0388684{col 70}{space 3}  .131997
{txt}{space 10}phone {c |}{col 17}{res}{space 2} -.070993{col 29}{space 2} .0406927{col 40}{space 1}   -1.74{col 49}{space 3}0.081{col 57}{space 4}-.1507731{col 70}{space 3}  .008787
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .142286{col 29}{space 2} .0409117{col 40}{space 1}    3.48{col 49}{space 3}0.001{col 57}{space 4} .0620767{col 70}{space 3} .2224952
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}  .080568{col 29}{space 2} .0437561{col 40}{space 1}    1.84{col 49}{space 3}0.066{col 57}{space 4}-.0052178{col 70}{space 3} .1663539
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.0147947{col 29}{space 2} .0375491{col 40}{space 1}   -0.39{col 49}{space 3}0.694{col 57}{space 4}-.0884115{col 70}{space 3} .0588221
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0421093{col 29}{space 2} .0406433{col 40}{space 1}    1.04{col 49}{space 3}0.300{col 57}{space 4}-.0375739{col 70}{space 3} .1217924
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0049307{col 29}{space 2} .0018277{col 40}{space 1}    2.70{col 49}{space 3}0.007{col 57}{space 4} .0013475{col 70}{space 3} .0085139
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .3200753{col 29}{space 2} .2169523{col 40}{space 1}    1.48{col 49}{space 3}0.140{col 57}{space 4}-.1052699{col 70}{space 3} .7454204
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .3956354{col 29}{space 2} .0221106{col 40}{space 1}   17.89{col 49}{space 3}0.000{col 57}{space 4} .3522867{col 70}{space 3} .4389842
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .3764397{col 29}{space 2} .1615688{col 40}{space 1}    2.33{col 49}{space 3}0.020{col 57}{space 4} .0596764{col 70}{space 3} .6932029
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} .79341776
        {txt}sigma_e {c |} {res} .76186721
            {txt}rho {c |} {res} .52027768{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    18,429
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,218

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.1008{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.3728{col 63}{txt}avg{col 67}={col 69}{res}       2.2
{txt}     overall = {res}0.3344{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}8217{txt}){col 67}={col 70}{res}    49.23
{txt}corr(u_i, Xb){col 16}= {res}0.3396{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2326423{col 29}{space 2} .0118519{col 40}{space 1}   19.63{col 49}{space 3}0.000{col 57}{space 4} .2094095{col 70}{space 3}  .255875
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0063096{col 29}{space 2} .0067216{col 40}{space 1}    0.94{col 49}{space 3}0.348{col 57}{space 4}-.0068665{col 70}{space 3} .0194858
{txt}dependent_share {c |}{col 17}{res}{space 2} .0260653{col 29}{space 2} .0557598{col 40}{space 1}    0.47{col 49}{space 3}0.640{col 57}{space 4} -.083238{col 70}{space 3} .1353685
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0009786{col 29}{space 2} .0013723{col 40}{space 1}   -0.71{col 49}{space 3}0.476{col 57}{space 4}-.0036687{col 70}{space 3} .0017115
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0336401{col 29}{space 2} .0469644{col 40}{space 1}   -0.72{col 49}{space 3}0.474{col 57}{space 4}-.1257023{col 70}{space 3}  .058422
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}-.0097181{col 29}{space 2} .0270759{col 40}{space 1}   -0.36{col 49}{space 3}0.720{col 57}{space 4}-.0627936{col 70}{space 3} .0433575
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.0511334{col 29}{space 2} .0266254{col 40}{space 1}   -1.92{col 49}{space 3}0.055{col 57}{space 4} -.103326{col 70}{space 3} .0010592
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .0532112{col 29}{space 2}  .026634{col 40}{space 1}    2.00{col 49}{space 3}0.046{col 57}{space 4} .0010019{col 70}{space 3} .1054205
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.0039138{col 29}{space 2} .0323911{col 40}{space 1}   -0.12{col 49}{space 3}0.904{col 57}{space 4}-.0674086{col 70}{space 3}  .059581
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0031039{col 29}{space 2}  .029467{col 40}{space 1}    0.11{col 49}{space 3}0.916{col 57}{space 4}-.0546588{col 70}{space 3} .0608667
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .0276015{col 29}{space 2} .0279296{col 40}{space 1}    0.99{col 49}{space 3}0.323{col 57}{space 4}-.0271477{col 70}{space 3} .0823506
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0243998{col 29}{space 2} .0447864{col 40}{space 1}    0.54{col 49}{space 3}0.586{col 57}{space 4}-.0633928{col 70}{space 3} .1121925
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0248421{col 29}{space 2} .0084399{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} .0082978{col 70}{space 3} .0413863
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0187345{col 29}{space 2} .0750353{col 40}{space 1}    0.25{col 49}{space 3}0.803{col 57}{space 4}-.1283537{col 70}{space 3} .1658228
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.5767141{col 29}{space 2} .0371104{col 40}{space 1}  -15.54{col 49}{space 3}0.000{col 57}{space 4}-.6494599{col 70}{space 3}-.5039683
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.3455732{col 29}{space 2}   .03574{col 40}{space 1}   -9.67{col 49}{space 3}0.000{col 57}{space 4}-.4156327{col 70}{space 3}-.2755137
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.3656921{col 29}{space 2} .0355864{col 40}{space 1}  -10.28{col 49}{space 3}0.000{col 57}{space 4}-.4354504{col 70}{space 3}-.2959338
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.083346{col 29}{space 2} .0933765{col 40}{space 1}   11.60{col 49}{space 3}0.000{col 57}{space 4}  .900304{col 70}{space 3} 1.266387
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} .97605744
        {txt}sigma_e {c |} {res} .85452267
            {txt}rho {c |} {res} .56610004{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    17,046
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,817

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.1146{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.6354{col 63}{txt}avg{col 67}={col 69}{res}       1.9
{txt}     overall = {res}0.5482{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}17{txt},{res}8816{txt}){col 67}={col 70}{res}    44.29
{txt}corr(u_i, Xb){col 16}= {res}0.5024{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .3035556{col 29}{space 2} .0121663{col 40}{space 1}   24.95{col 49}{space 3}0.000{col 57}{space 4} .2797068{col 70}{space 3} .3274043
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0329732{col 29}{space 2} .0094147{col 40}{space 1}    3.50{col 49}{space 3}0.000{col 57}{space 4} .0145181{col 70}{space 3} .0514282
{txt}dependent_share {c |}{col 17}{res}{space 2}-.0687399{col 29}{space 2} .0817148{col 40}{space 1}   -0.84{col 49}{space 3}0.400{col 57}{space 4}-.2289199{col 70}{space 3} .0914402
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} -.002384{col 29}{space 2} .0024178{col 40}{space 1}   -0.99{col 49}{space 3}0.324{col 57}{space 4}-.0071234{col 70}{space 3} .0023554
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0736065{col 29}{space 2} .0623235{col 40}{space 1}   -1.18{col 49}{space 3}0.238{col 57}{space 4}-.1957752{col 70}{space 3} .0485622
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0660124{col 29}{space 2} .0495183{col 40}{space 1}    1.33{col 49}{space 3}0.183{col 57}{space 4}-.0310549{col 70}{space 3} .1630797
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0711294{col 29}{space 2} .0547926{col 40}{space 1}    1.30{col 49}{space 3}0.194{col 57}{space 4}-.0362769{col 70}{space 3} .1785357
{txt}{space 10}phone {c |}{col 17}{res}{space 2}-.0317256{col 29}{space 2} .0372946{col 40}{space 1}   -0.85{col 49}{space 3}0.395{col 57}{space 4}-.1048318{col 70}{space 3} .0413806
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}-.1596462{col 29}{space 2} .0439704{col 40}{space 1}   -3.63{col 49}{space 3}0.000{col 57}{space 4}-.2458386{col 70}{space 3}-.0734539
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0173638{col 29}{space 2} .0281346{col 40}{space 1}   -0.62{col 49}{space 3}0.537{col 57}{space 4}-.0725142{col 70}{space 3} .0377867
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .0187289{col 29}{space 2} .0291114{col 40}{space 1}    0.64{col 49}{space 3}0.520{col 57}{space 4}-.0383362{col 70}{space 3}  .075794
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0332926{col 29}{space 2} .0345438{col 40}{space 1}   -0.96{col 49}{space 3}0.335{col 57}{space 4}-.1010065{col 70}{space 3} .0344212
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0124456{col 29}{space 2} .0045503{col 40}{space 1}    2.74{col 49}{space 3}0.006{col 57}{space 4}  .003526{col 70}{space 3} .0213652
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0198731{col 29}{space 2}  .043434{col 40}{space 1}    0.46{col 49}{space 3}0.647{col 57}{space 4}-.0652676{col 70}{space 3} .1050138
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2} .0479519{col 29}{space 2} .0264859{col 40}{space 1}    1.81{col 49}{space 3}0.070{col 57}{space 4}-.0039667{col 70}{space 3} .0998705
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.0165104{col 29}{space 2} .0219008{col 40}{space 1}   -0.75{col 49}{space 3}0.451{col 57}{space 4}-.0594411{col 70}{space 3} .0264204
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2}-.0337952{col 29}{space 2}  .037483{col 40}{space 1}   -0.90{col 49}{space 3}0.367{col 57}{space 4}-.1072707{col 70}{space 3} .0396803
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .8847832{col 29}{space 2} .1362402{col 40}{space 1}    6.49{col 49}{space 3}0.000{col 57}{space 4} .6177206{col 70}{space 3} 1.151846
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.1236107
        {txt}sigma_e {c |} {res} .99908067
            {txt}rho {c |} {res}  .5584649{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_own  pdd9   $xlist    $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    20,293
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,105

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0745{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.5942{col 63}{txt}avg{col 67}={col 69}{res}       4.0
{txt}     overall = {res}0.3877{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}19{txt},{res}5104{txt}){col 67}={col 70}{res}    47.70
{txt}corr(u_i, Xb){col 16}= {res}0.5053{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}       hdd9_own{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2272482{col 29}{space 2} .0104629{col 40}{space 1}   21.72{col 49}{space 3}0.000{col 57}{space 4} .2067365{col 70}{space 3} .2477599
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0460977{col 29}{space 2} .0075061{col 40}{space 1}    6.14{col 49}{space 3}0.000{col 57}{space 4} .0313826{col 70}{space 3} .0608128
{txt}dependent_share {c |}{col 17}{res}{space 2}-.0010317{col 29}{space 2} .0658806{col 40}{space 1}   -0.02{col 49}{space 3}0.988{col 57}{space 4}-.1301859{col 70}{space 3} .1281225
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0067989{col 29}{space 2} .0021755{col 40}{space 1}    3.13{col 49}{space 3}0.002{col 57}{space 4} .0025339{col 70}{space 3} .0110639
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0010953{col 29}{space 2} .0515429{col 40}{space 1}    0.02{col 49}{space 3}0.983{col 57}{space 4}-.0999509{col 70}{space 3} .1021415
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1461719{col 29}{space 2} .0368739{col 40}{space 1}    3.96{col 49}{space 3}0.000{col 57}{space 4} .0738833{col 70}{space 3} .2184605
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0179652{col 29}{space 2}  .045782{col 40}{space 1}    0.39{col 49}{space 3}0.695{col 57}{space 4}-.0717872{col 70}{space 3} .1077175
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1108598{col 29}{space 2} .0313019{col 40}{space 1}    3.54{col 49}{space 3}0.000{col 57}{space 4} .0494947{col 70}{space 3} .1722249
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0723818{col 29}{space 2} .0310993{col 40}{space 1}    2.33{col 49}{space 3}0.020{col 57}{space 4} .0114138{col 70}{space 3} .1333497
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.1719759{col 29}{space 2} .0247852{col 40}{space 1}   -6.94{col 49}{space 3}0.000{col 57}{space 4}-.2205656{col 70}{space 3}-.1233863
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.0294244{col 29}{space 2} .0280695{col 40}{space 1}   -1.05{col 49}{space 3}0.295{col 57}{space 4}-.0844527{col 70}{space 3} .0256039
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0045232{col 29}{space 2}  .025385{col 40}{space 1}   -0.18{col 49}{space 3}0.859{col 57}{space 4}-.0542887{col 70}{space 3} .0452423
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .000577{col 29}{space 2} .0014408{col 40}{space 1}    0.40{col 49}{space 3}0.689{col 57}{space 4}-.0022477{col 70}{space 3} .0034016
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0939351{col 29}{space 2} .0335979{col 40}{space 1}    2.80{col 49}{space 3}0.005{col 57}{space 4} .0280689{col 70}{space 3} .1598014
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.0450155{col 29}{space 2} .0291058{col 40}{space 1}   -1.55{col 49}{space 3}0.122{col 57}{space 4}-.1020754{col 70}{space 3} .0120444
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .1425977{col 29}{space 2} .0295893{col 40}{space 1}    4.82{col 49}{space 3}0.000{col 57}{space 4}   .08459{col 70}{space 3} .2006054
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}  .349137{col 29}{space 2} .0290814{col 40}{space 1}   12.01{col 49}{space 3}0.000{col 57}{space 4}  .292125{col 70}{space 3} .4061489
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .2043974{col 29}{space 2} .0283992{col 40}{space 1}    7.20{col 49}{space 3}0.000{col 57}{space 4} .1487228{col 70}{space 3}  .260072
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2844649{col 29}{space 2}  .028051{col 40}{space 1}   10.14{col 49}{space 3}0.000{col 57}{space 4} .2294728{col 70}{space 3} .3394569
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .9440461{col 29}{space 2} .1229837{col 40}{space 1}    7.68{col 49}{space 3}0.000{col 57}{space 4} .7029453{col 70}{space 3} 1.185147
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.1855393
        {txt}sigma_e {c |} {res} 1.1715101
            {txt}rho {c |} {res} .50595179{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S22_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S22_fe.rtf not found)
(output written to {browse  `"S22_fe.rtf"'})

{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S23                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9_purchase  pdd9   $xlist    i.year  , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    82,550
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    34,744

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0333{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2576{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.2016{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}24{txt},{res}34743{txt}){col 67}={col 70}{res}    56.73
{txt}corr(u_i, Xb){col 16}= {res}0.3244{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}-.0017376{col 29}{space 2} .0064049{col 40}{space 1}   -0.27{col 49}{space 3}0.786{col 57}{space 4}-.0142914{col 70}{space 3} .0108161
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0277086{col 29}{space 2} .0050588{col 40}{space 1}    5.48{col 49}{space 3}0.000{col 57}{space 4} .0177932{col 70}{space 3}  .037624
{txt}dependent_share {c |}{col 17}{res}{space 2} .0285263{col 29}{space 2} .0445152{col 40}{space 1}    0.64{col 49}{space 3}0.522{col 57}{space 4} -.058725{col 70}{space 3} .1157776
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0079704{col 29}{space 2} .0014183{col 40}{space 1}   -5.62{col 49}{space 3}0.000{col 57}{space 4}-.0107503{col 70}{space 3}-.0051906
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1517301{col 29}{space 2} .0364506{col 40}{space 1}   -4.16{col 49}{space 3}0.000{col 57}{space 4}-.2231745{col 70}{space 3}-.0802857
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0776479{col 29}{space 2} .0229138{col 40}{space 1}    3.39{col 49}{space 3}0.001{col 57}{space 4} .0327361{col 70}{space 3} .1225596
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1118141{col 29}{space 2} .0289613{col 40}{space 1}    3.86{col 49}{space 3}0.000{col 57}{space 4} .0550489{col 70}{space 3} .1685792
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2397817{col 29}{space 2}   .02021{col 40}{space 1}   11.86{col 49}{space 3}0.000{col 57}{space 4} .2001695{col 70}{space 3}  .279394
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2401196{col 29}{space 2} .0243243{col 40}{space 1}    9.87{col 49}{space 3}0.000{col 57}{space 4} .1924431{col 70}{space 3}  .287796
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2079485{col 29}{space 2} .0193974{col 40}{space 1}   10.72{col 49}{space 3}0.000{col 57}{space 4} .1699289{col 70}{space 3}  .245968
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2832443{col 29}{space 2} .0187546{col 40}{space 1}   15.10{col 49}{space 3}0.000{col 57}{space 4} .2464848{col 70}{space 3} .3200039
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0814618{col 29}{space 2} .0185842{col 40}{space 1}    4.38{col 49}{space 3}0.000{col 57}{space 4} .0450362{col 70}{space 3} .1178874
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .002765{col 29}{space 2} .0012693{col 40}{space 1}    2.18{col 49}{space 3}0.029{col 57}{space 4} .0002771{col 70}{space 3} .0052529
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0337059{col 29}{space 2} .0250495{col 40}{space 1}   -1.35{col 49}{space 3}0.178{col 57}{space 4}-.0828037{col 70}{space 3}  .015392
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1437345{col 29}{space 2} .0452857{col 40}{space 1}   -3.17{col 49}{space 3}0.002{col 57}{space 4}-.2324959{col 70}{space 3} -.054973
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .0711751{col 29}{space 2} .0317403{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4}  .008963{col 70}{space 3} .1333871
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .0815307{col 29}{space 2} .0393123{col 40}{space 1}    2.07{col 49}{space 3}0.038{col 57}{space 4} .0044773{col 70}{space 3} .1585841
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0400176{col 29}{space 2} .0327421{col 40}{space 1}    1.22{col 49}{space 3}0.222{col 57}{space 4}-.0241579{col 70}{space 3} .1041931
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2554317{col 29}{space 2} .0391834{col 40}{space 1}    6.52{col 49}{space 3}0.000{col 57}{space 4}  .178631{col 70}{space 3} .3322324
{txt}{space 10}2014  {c |}{col 17}{res}{space 2}   .19969{col 29}{space 2} .0470682{col 40}{space 1}    4.24{col 49}{space 3}0.000{col 57}{space 4} .1074347{col 70}{space 3} .2919452
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3481169{col 29}{space 2} .0373108{col 40}{space 1}    9.33{col 49}{space 3}0.000{col 57}{space 4} .2749866{col 70}{space 3} .4212472
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .2675903{col 29}{space 2} .0521922{col 40}{space 1}    5.13{col 49}{space 3}0.000{col 57}{space 4} .1652919{col 70}{space 3} .3698887
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .4518429{col 29}{space 2} .0443274{col 40}{space 1}   10.19{col 49}{space 3}0.000{col 57}{space 4} .3649598{col 70}{space 3} .5387261
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .4322862{col 29}{space 2} .0439926{col 40}{space 1}    9.83{col 49}{space 3}0.000{col 57}{space 4} .3460592{col 70}{space 3} .5185132
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.037265{col 29}{space 2} .0788998{col 40}{space 1}   51.17{col 49}{space 3}0.000{col 57}{space 4} 3.882618{col 70}{space 3} 4.191911
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.8771033
        {txt}sigma_e {c |} {res} 1.3909744
            {txt}rho {c |} {res} .64553059{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    10,583
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,088

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0479{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1501{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.1322{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}15{txt},{res}5087{txt}){col 67}={col 70}{res}    18.11
{txt}corr(u_i, Xb){col 16}= {res}0.2109{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0404713{col 29}{space 2} .0131972{col 40}{space 1}    3.07{col 49}{space 3}0.002{col 57}{space 4}  .014599{col 70}{space 3} .0663435
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0314665{col 29}{space 2} .0160155{col 40}{space 1}    1.96{col 49}{space 3}0.049{col 57}{space 4} .0000692{col 70}{space 3} .0628638
{txt}dependent_share {c |}{col 17}{res}{space 2}-.0896086{col 29}{space 2} .1146614{col 40}{space 1}   -0.78{col 49}{space 3}0.435{col 57}{space 4}-.3143943{col 70}{space 3}  .135177
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0118052{col 29}{space 2} .0033746{col 40}{space 1}    3.50{col 49}{space 3}0.000{col 57}{space 4} .0051895{col 70}{space 3}  .018421
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0569451{col 29}{space 2} .1004138{col 40}{space 1}   -0.57{col 49}{space 3}0.571{col 57}{space 4}-.2537994{col 70}{space 3} .1399092
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1536893{col 29}{space 2} .0565121{col 40}{space 1}    2.72{col 49}{space 3}0.007{col 57}{space 4} .0429014{col 70}{space 3} .2644773
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0638407{col 29}{space 2} .1725695{col 40}{space 1}    0.37{col 49}{space 3}0.711{col 57}{space 4}-.2744697{col 70}{space 3} .4021512
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1968324{col 29}{space 2}  .044804{col 40}{space 1}    4.39{col 49}{space 3}0.000{col 57}{space 4} .1089973{col 70}{space 3} .2846674
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .3506479{col 29}{space 2}  .053773{col 40}{space 1}    6.52{col 49}{space 3}0.000{col 57}{space 4} .2452297{col 70}{space 3} .4560661
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}-.0602747{col 29}{space 2} .0640625{col 40}{space 1}   -0.94{col 49}{space 3}0.347{col 57}{space 4}-.1858647{col 70}{space 3} .0653153
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .3095278{col 29}{space 2} .0603099{col 40}{space 1}    5.13{col 49}{space 3}0.000{col 57}{space 4} .1912944{col 70}{space 3} .4277611
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0808412{col 29}{space 2} .0441024{col 40}{space 1}    1.83{col 49}{space 3}0.067{col 57}{space 4}-.0056185{col 70}{space 3} .1673009
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}-.0096647{col 29}{space 2} .0062639{col 40}{space 1}   -1.54{col 49}{space 3}0.123{col 57}{space 4}-.0219447{col 70}{space 3} .0026153
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0555343{col 29}{space 2} .0539129{col 40}{space 1}   -1.03{col 49}{space 3}0.303{col 57}{space 4}-.1612268{col 70}{space 3} .0501583
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.2315278{col 29}{space 2} .0256802{col 40}{space 1}   -9.02{col 49}{space 3}0.000{col 57}{space 4}-.2818721{col 70}{space 3}-.1811835
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  2.03646{col 29}{space 2} .1775485{col 40}{space 1}   11.47{col 49}{space 3}0.000{col 57}{space 4} 1.688389{col 70}{space 3} 2.384532
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.7910457
        {txt}sigma_e {c |} {res} 1.1082993
            {txt}rho {c |} {res} .72311099{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_MALAWI if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     9,155
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,447

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0511{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.4477{col 63}{txt}avg{col 67}={col 69}{res}       2.7
{txt}     overall = {res}0.3644{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}16{txt},{res}3446{txt}){col 67}={col 70}{res}    16.53
{txt}corr(u_i, Xb){col 16}= {res}0.4748{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}-.0156464{col 29}{space 2} .0172294{col 40}{space 1}   -0.91{col 49}{space 3}0.364{col 57}{space 4}-.0494273{col 70}{space 3} .0181344
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0207354{col 29}{space 2} .0156599{col 40}{space 1}    1.32{col 49}{space 3}0.186{col 57}{space 4}-.0099682{col 70}{space 3}  .051439
{txt}dependent_share {c |}{col 17}{res}{space 2}-.3355633{col 29}{space 2} .1119601{col 40}{space 1}   -3.00{col 49}{space 3}0.003{col 57}{space 4}-.5550781{col 70}{space 3}-.1160484
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}  -.00971{col 29}{space 2} .0036833{col 40}{space 1}   -2.64{col 49}{space 3}0.008{col 57}{space 4}-.0169317{col 70}{space 3}-.0024883
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1930901{col 29}{space 2} .0791535{col 40}{space 1}   -2.44{col 49}{space 3}0.015{col 57}{space 4}-.3482826{col 70}{space 3}-.0378975
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1330639{col 29}{space 2} .0687487{col 40}{space 1}    1.94{col 49}{space 3}0.053{col 57}{space 4}-.0017283{col 70}{space 3} .2678562
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2164635{col 29}{space 2} .1452651{col 40}{space 1}    1.49{col 49}{space 3}0.136{col 57}{space 4}-.0683509{col 70}{space 3} .5012778
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .4276646{col 29}{space 2} .0605195{col 40}{space 1}    7.07{col 49}{space 3}0.000{col 57}{space 4}  .309007{col 70}{space 3} .5463223
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .5284537{col 29}{space 2} .0964929{col 40}{space 1}    5.48{col 49}{space 3}0.000{col 57}{space 4} .3392646{col 70}{space 3} .7176429
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .3220174{col 29}{space 2} .0650008{col 40}{space 1}    4.95{col 49}{space 3}0.000{col 57}{space 4} .1945735{col 70}{space 3} .4494613
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .3665194{col 29}{space 2} .0492976{col 40}{space 1}    7.43{col 49}{space 3}0.000{col 57}{space 4} .2698641{col 70}{space 3} .4631748
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0116003{col 29}{space 2} .0455811{col 40}{space 1}   -0.25{col 49}{space 3}0.799{col 57}{space 4}-.1009691{col 70}{space 3} .0777685
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}-.0162934{col 29}{space 2} .0388664{col 40}{space 1}   -0.42{col 49}{space 3}0.675{col 57}{space 4}-.0924969{col 70}{space 3} .0599101
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1063559{col 29}{space 2} .0691003{col 40}{space 1}    1.54{col 49}{space 3}0.124{col 57}{space 4}-.0291259{col 70}{space 3} .2418376
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.2735677{col 29}{space 2} .0573128{col 40}{space 1}   -4.77{col 49}{space 3}0.000{col 57}{space 4}-.3859381{col 70}{space 3}-.1611973
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} -.040507{col 29}{space 2} .0443434{col 40}{space 1}   -0.91{col 49}{space 3}0.361{col 57}{space 4}-.1274489{col 70}{space 3}  .046435
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.924845{col 29}{space 2} .1983128{col 40}{space 1}   24.83{col 49}{space 3}0.000{col 57}{space 4} 4.536022{col 70}{space 3} 5.313668
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.7145821
        {txt}sigma_e {c |} {res}  1.489792
            {txt}rho {c |} {res} .56980748{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     7,044
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,069

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0278{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0100{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0136{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}15{txt},{res}4068{txt}){col 67}={col 70}{res}     5.21
{txt}corr(u_i, Xb){col 16}= {res}-0.0744{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2361543{col 29}{space 2} .0382322{col 40}{space 1}    6.18{col 49}{space 3}0.000{col 57}{space 4} .1611982{col 70}{space 3} .3111104
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0363773{col 29}{space 2} .0193545{col 40}{space 1}   -1.88{col 49}{space 3}0.060{col 57}{space 4}-.0743227{col 70}{space 3} .0015681
{txt}dependent_share {c |}{col 17}{res}{space 2} .0474905{col 29}{space 2} .2438699{col 40}{space 1}    0.19{col 49}{space 3}0.846{col 57}{space 4} -.430628{col 70}{space 3} .5256089
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0030923{col 29}{space 2} .0062158{col 40}{space 1}    0.50{col 49}{space 3}0.619{col 57}{space 4}-.0090941{col 70}{space 3} .0152788
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}  .260155{col 29}{space 2} .1625135{col 40}{space 1}    1.60{col 49}{space 3}0.109{col 57}{space 4}-.0584605{col 70}{space 3} .5787704
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1530903{col 29}{space 2} .0897154{col 40}{space 1}    1.71{col 49}{space 3}0.088{col 57}{space 4}-.0228011{col 70}{space 3} .3289816
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}  .256123{col 29}{space 2} .0992848{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0614704{col 70}{space 3} .4507756
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1761279{col 29}{space 2} .0816407{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} .0160674{col 70}{space 3} .3361883
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2369011{col 29}{space 2} .1080475{col 40}{space 1}    2.19{col 49}{space 3}0.028{col 57}{space 4} .0250689{col 70}{space 3} .4487334
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2961662{col 29}{space 2}  .088923{col 40}{space 1}    3.33{col 49}{space 3}0.001{col 57}{space 4} .1218285{col 70}{space 3} .4705039
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1567504{col 29}{space 2}  .071926{col 40}{space 1}   -2.18{col 49}{space 3}0.029{col 57}{space 4}-.2977648{col 70}{space 3} -.015736
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0353748{col 29}{space 2} .0724474{col 40}{space 1}   -0.49{col 49}{space 3}0.625{col 57}{space 4}-.1774113{col 70}{space 3} .1066618
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0040198{col 29}{space 2}  .002567{col 40}{space 1}    1.57{col 49}{space 3}0.117{col 57}{space 4}-.0010129{col 70}{space 3} .0090525
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0112173{col 29}{space 2} .3338759{col 40}{space 1}   -0.03{col 49}{space 3}0.973{col 57}{space 4}-.6657968{col 70}{space 3} .6433622
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .0534993{col 29}{space 2}  .046197{col 40}{space 1}    1.16{col 49}{space 3}0.247{col 57}{space 4}-.0370721{col 70}{space 3} .1440708
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  4.59096{col 29}{space 2} .3405448{col 40}{space 1}   13.48{col 49}{space 3}0.000{col 57}{space 4} 3.923306{col 70}{space 3} 5.258614
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.6786736
        {txt}sigma_e {c |} {res} 1.5029883
            {txt}rho {c |} {res} .55505027{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    18,429
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,218

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0305{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1162{col 63}{txt}avg{col 67}={col 69}{res}       2.2
{txt}     overall = {res}0.0988{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}8217{txt}){col 67}={col 70}{res}    17.80
{txt}corr(u_i, Xb){col 16}= {res}0.1474{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}   .00385{col 29}{space 2} .0160265{col 40}{space 1}    0.24{col 49}{space 3}0.810{col 57}{space 4} -.027566{col 70}{space 3} .0352659
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0480984{col 29}{space 2} .0103278{col 40}{space 1}    4.66{col 49}{space 3}0.000{col 57}{space 4} .0278533{col 70}{space 3} .0683434
{txt}dependent_share {c |}{col 17}{res}{space 2} .0783723{col 29}{space 2}  .088591{col 40}{space 1}    0.88{col 49}{space 3}0.376{col 57}{space 4}-.0952885{col 70}{space 3} .2520331
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0020243{col 29}{space 2} .0022893{col 40}{space 1}   -0.88{col 49}{space 3}0.377{col 57}{space 4} -.006512{col 70}{space 3} .0024634
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.2358916{col 29}{space 2} .0796068{col 40}{space 1}   -2.96{col 49}{space 3}0.003{col 57}{space 4} -.391941{col 70}{space 3}-.0798422
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0881376{col 29}{space 2} .0412828{col 40}{space 1}    2.13{col 49}{space 3}0.033{col 57}{space 4} .0072129{col 70}{space 3} .1690623
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}  .031437{col 29}{space 2}  .041997{col 40}{space 1}    0.75{col 49}{space 3}0.454{col 57}{space 4}-.0508876{col 70}{space 3} .1137616
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2119709{col 29}{space 2} .0420774{col 40}{space 1}    5.04{col 49}{space 3}0.000{col 57}{space 4} .1294884{col 70}{space 3} .2944533
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1404933{col 29}{space 2} .0498109{col 40}{space 1}    2.82{col 49}{space 3}0.005{col 57}{space 4} .0428513{col 70}{space 3} .2381353
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1985185{col 29}{space 2} .0529385{col 40}{space 1}    3.75{col 49}{space 3}0.000{col 57}{space 4} .0947456{col 70}{space 3} .3022913
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .3092288{col 29}{space 2}  .043718{col 40}{space 1}    7.07{col 49}{space 3}0.000{col 57}{space 4} .2235305{col 70}{space 3} .3949272
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0041605{col 29}{space 2} .0656894{col 40}{space 1}    0.06{col 49}{space 3}0.950{col 57}{space 4}-.1246073{col 70}{space 3} .1329283
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}-.0158927{col 29}{space 2} .0107446{col 40}{space 1}   -1.48{col 49}{space 3}0.139{col 57}{space 4}-.0369548{col 70}{space 3} .0051694
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1411584{col 29}{space 2} .1068486{col 40}{space 1}    1.32{col 49}{space 3}0.187{col 57}{space 4}-.0682918{col 70}{space 3} .3506086
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.2611762{col 29}{space 2} .0542476{col 40}{space 1}   -4.81{col 49}{space 3}0.000{col 57}{space 4}-.3675152{col 70}{space 3}-.1548372
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.3654385{col 29}{space 2} .0525446{col 40}{space 1}   -6.95{col 49}{space 3}0.000{col 57}{space 4}-.4684393{col 70}{space 3}-.2624378
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.0675855{col 29}{space 2} .0515973{col 40}{space 1}   -1.31{col 49}{space 3}0.190{col 57}{space 4}-.1687293{col 70}{space 3} .0335583
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.730396{col 29}{space 2} .1525929{col 40}{space 1}   31.00{col 49}{space 3}0.000{col 57}{space 4} 4.431275{col 70}{space 3} 5.029516
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.7305865
        {txt}sigma_e {c |} {res} 1.3723453
            {txt}rho {c |} {res} .61393384{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    17,046
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     8,817

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0320{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1927{col 63}{txt}avg{col 67}={col 69}{res}       1.9
{txt}     overall = {res}0.1827{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}17{txt},{res}8816{txt}){col 67}={col 70}{res}    13.64
{txt}corr(u_i, Xb){col 16}= {res}0.2530{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}-.0067653{col 29}{space 2} .0144509{col 40}{space 1}   -0.47{col 49}{space 3}0.640{col 57}{space 4}-.0350924{col 70}{space 3} .0215618
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0293235{col 29}{space 2} .0113626{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0070502{col 70}{space 3} .0515968
{txt}dependent_share {c |}{col 17}{res}{space 2}   .32965{col 29}{space 2} .1144138{col 40}{space 1}    2.88{col 49}{space 3}0.004{col 57}{space 4} .1053723{col 70}{space 3} .5539276
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0178541{col 29}{space 2} .0033615{col 40}{space 1}   -5.31{col 49}{space 3}0.000{col 57}{space 4}-.0244435{col 70}{space 3}-.0112647
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0989862{col 29}{space 2} .0945294{col 40}{space 1}   -1.05{col 49}{space 3}0.295{col 57}{space 4}-.2842858{col 70}{space 3} .0863134
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}  .072241{col 29}{space 2} .0644029{col 40}{space 1}    1.12{col 49}{space 3}0.262{col 57}{space 4}-.0540038{col 70}{space 3} .1984858
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0678882{col 29}{space 2} .0771008{col 40}{space 1}    0.88{col 49}{space 3}0.379{col 57}{space 4}-.0832474{col 70}{space 3} .2190238
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .3566413{col 29}{space 2} .0475457{col 40}{space 1}    7.50{col 49}{space 3}0.000{col 57}{space 4} .2634406{col 70}{space 3}  .449842
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1435839{col 29}{space 2} .0616722{col 40}{space 1}    2.33{col 49}{space 3}0.020{col 57}{space 4}  .022692{col 70}{space 3} .2644757
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1768132{col 29}{space 2} .0372826{col 40}{space 1}    4.74{col 49}{space 3}0.000{col 57}{space 4} .1037305{col 70}{space 3} .2498958
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .3046222{col 29}{space 2} .0405574{col 40}{space 1}    7.51{col 49}{space 3}0.000{col 57}{space 4} .2251202{col 70}{space 3} .3841242
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0245787{col 29}{space 2} .0451915{col 40}{space 1}    0.54{col 49}{space 3}0.587{col 57}{space 4}-.0640072{col 70}{space 3} .1131645
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0105824{col 29}{space 2} .0042451{col 40}{space 1}    2.49{col 49}{space 3}0.013{col 57}{space 4} .0022611{col 70}{space 3} .0189037
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0786649{col 29}{space 2}  .051502{col 40}{space 1}   -1.53{col 49}{space 3}0.127{col 57}{space 4}-.1796208{col 70}{space 3}  .022291
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.0958891{col 29}{space 2} .0350672{col 40}{space 1}   -2.73{col 49}{space 3}0.006{col 57}{space 4} -.164629{col 70}{space 3}-.0271493
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.0429633{col 29}{space 2} .0302824{col 40}{space 1}   -1.42{col 49}{space 3}0.156{col 57}{space 4}-.1023238{col 70}{space 3} .0163972
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1366229{col 29}{space 2} .0520691{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} .0345552{col 70}{space 3} .2386905
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.601327{col 29}{space 2} .1831181{col 40}{space 1}   25.13{col 49}{space 3}0.000{col 57}{space 4} 4.242373{col 70}{space 3} 4.960281
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.9644447
        {txt}sigma_e {c |} {res} 1.3411357
            {txt}rho {c |} {res} .68208832{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9_purchase  pdd9   $xlist   $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    20,293
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,105

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0395{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.3534{col 63}{txt}avg{col 67}={col 69}{res}       4.0
{txt}     overall = {res}0.2147{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}19{txt},{res}5104{txt}){col 67}={col 70}{res}    27.85
{txt}corr(u_i, Xb){col 16}= {res}0.3616{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  hdd9_purchase{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2}-.0105309{col 29}{space 2} .0119843{col 40}{space 1}   -0.88{col 49}{space 3}0.380{col 57}{space 4}-.0340254{col 70}{space 3} .0129635
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0126158{col 29}{space 2} .0088566{col 40}{space 1}    1.42{col 49}{space 3}0.154{col 57}{space 4}-.0047469{col 70}{space 3} .0299786
{txt}dependent_share {c |}{col 17}{res}{space 2} .0451565{col 29}{space 2} .0834407{col 40}{space 1}    0.54{col 49}{space 3}0.588{col 57}{space 4}-.1184231{col 70}{space 3} .2087361
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0009896{col 29}{space 2} .0029758{col 40}{space 1}   -0.33{col 49}{space 3}0.739{col 57}{space 4}-.0068233{col 70}{space 3} .0048442
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0161447{col 29}{space 2} .0663107{col 40}{space 1}    0.24{col 49}{space 3}0.808{col 57}{space 4}-.1138527{col 70}{space 3}  .146142
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0775965{col 29}{space 2} .0446475{col 40}{space 1}    1.74{col 49}{space 3}0.082{col 57}{space 4}-.0099317{col 70}{space 3} .1651247
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2626884{col 29}{space 2} .0581406{col 40}{space 1}    4.52{col 49}{space 3}0.000{col 57}{space 4} .1487079{col 70}{space 3} .3766688
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2889848{col 29}{space 2} .0381816{col 40}{space 1}    7.57{col 49}{space 3}0.000{col 57}{space 4} .2141326{col 70}{space 3} .3638371
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .4504568{col 29}{space 2}  .040096{col 40}{space 1}   11.23{col 49}{space 3}0.000{col 57}{space 4} .3718515{col 70}{space 3} .5290622
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2020215{col 29}{space 2} .0312352{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .1407872{col 70}{space 3} .2632557
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2798965{col 29}{space 2} .0336557{col 40}{space 1}    8.32{col 49}{space 3}0.000{col 57}{space 4} .2139169{col 70}{space 3} .3458762
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0817628{col 29}{space 2} .0295415{col 40}{space 1}    2.77{col 49}{space 3}0.006{col 57}{space 4} .0238487{col 70}{space 3} .1396768
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0015045{col 29}{space 2} .0015092{col 40}{space 1}    1.00{col 49}{space 3}0.319{col 57}{space 4}-.0014543{col 70}{space 3} .0044633
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0482845{col 29}{space 2} .0400503{col 40}{space 1}   -1.21{col 49}{space 3}0.228{col 57}{space 4}-.1268002{col 70}{space 3} .0302312
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1474432{col 29}{space 2} .0364346{col 40}{space 1}   -4.05{col 49}{space 3}0.000{col 57}{space 4}-.2188708{col 70}{space 3}-.0760157
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.1187946{col 29}{space 2} .0362771{col 40}{space 1}   -3.27{col 49}{space 3}0.001{col 57}{space 4}-.1899133{col 70}{space 3} -.047676
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .2336335{col 29}{space 2}  .036536{col 40}{space 1}    6.39{col 49}{space 3}0.000{col 57}{space 4} .1620073{col 70}{space 3} .3052598
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0349127{col 29}{space 2} .0361179{col 40}{space 1}    0.97{col 49}{space 3}0.334{col 57}{space 4}-.0358938{col 70}{space 3} .1057192
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .1707868{col 29}{space 2} .0344041{col 40}{space 1}    4.96{col 49}{space 3}0.000{col 57}{space 4} .1033399{col 70}{space 3} .2382337
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 3.303945{col 29}{space 2} .1649165{col 40}{space 1}   20.03{col 49}{space 3}0.000{col 57}{space 4} 2.980638{col 70}{space 3} 3.627252
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.6164399
        {txt}sigma_e {c |} {res} 1.4522365
            {txt}rho {c |} {res} .55335675{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. esttab using  S23_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S23_fe.rtf not found)
(output written to {browse  `"S23_fe.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                  S24                                         *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(24,163 observations deleted)

{com}. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9   $xlist    i.year  , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    65,579
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    27,229

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0359{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0962{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.0808{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}24{txt},{res}27228{txt}){col 67}={col 70}{res}    54.52
{txt}corr(u_i, Xb){col 16}= {res}0.1071{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1050431{col 29}{space 2} .0060055{col 40}{space 1}   17.49{col 49}{space 3}0.000{col 57}{space 4}  .093272{col 70}{space 3} .1168142
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0231623{col 29}{space 2}  .004925{col 40}{space 1}    4.70{col 49}{space 3}0.000{col 57}{space 4} .0135092{col 70}{space 3} .0328155
{txt}dependent_share {c |}{col 17}{res}{space 2} .1122255{col 29}{space 2} .0437739{col 40}{space 1}    2.56{col 49}{space 3}0.010{col 57}{space 4} .0264265{col 70}{space 3} .1980245
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0027507{col 29}{space 2} .0013379{col 40}{space 1}   -2.06{col 49}{space 3}0.040{col 57}{space 4} -.005373{col 70}{space 3}-.0001284
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} -.044619{col 29}{space 2} .0369316{col 40}{space 1}   -1.21{col 49}{space 3}0.227{col 57}{space 4}-.1170068{col 70}{space 3} .0277687
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1149459{col 29}{space 2} .0223906{col 40}{space 1}    5.13{col 49}{space 3}0.000{col 57}{space 4} .0710591{col 70}{space 3} .1588326
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1085379{col 29}{space 2} .0292755{col 40}{space 1}    3.71{col 49}{space 3}0.000{col 57}{space 4} .0511565{col 70}{space 3} .1659193
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1458947{col 29}{space 2}   .01938{col 40}{space 1}    7.53{col 49}{space 3}0.000{col 57}{space 4} .1079089{col 70}{space 3} .1838805
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1341554{col 29}{space 2} .0229379{col 40}{space 1}    5.85{col 49}{space 3}0.000{col 57}{space 4} .0891959{col 70}{space 3} .1791149
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1204996{col 29}{space 2} .0198176{col 40}{space 1}    6.08{col 49}{space 3}0.000{col 57}{space 4} .0816562{col 70}{space 3} .1593431
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2031388{col 29}{space 2} .0182246{col 40}{space 1}   11.15{col 49}{space 3}0.000{col 57}{space 4} .1674176{col 70}{space 3} .2388599
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0478917{col 29}{space 2} .0172411{col 40}{space 1}    2.78{col 49}{space 3}0.005{col 57}{space 4} .0140982{col 70}{space 3} .0816852
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0039679{col 29}{space 2}  .001685{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .0006652{col 70}{space 3} .0072706
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0109209{col 29}{space 2} .0232742{col 40}{space 1}    0.47{col 49}{space 3}0.639{col 57}{space 4}-.0346978{col 70}{space 3} .0565396
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1334125{col 29}{space 2} .0493875{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4}-.2302144{col 70}{space 3}-.0366105
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .1225246{col 29}{space 2} .0363925{col 40}{space 1}    3.37{col 49}{space 3}0.001{col 57}{space 4} .0511934{col 70}{space 3} .1938558
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2736945{col 29}{space 2} .0425274{col 40}{space 1}    6.44{col 49}{space 3}0.000{col 57}{space 4} .1903387{col 70}{space 3} .3570504
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1235358{col 29}{space 2} .0375022{col 40}{space 1}    3.29{col 49}{space 3}0.001{col 57}{space 4} .0500294{col 70}{space 3} .1970421
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2878126{col 29}{space 2} .0425566{col 40}{space 1}    6.76{col 49}{space 3}0.000{col 57}{space 4} .2043995{col 70}{space 3} .3712258
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .2189414{col 29}{space 2} .0481687{col 40}{space 1}    4.55{col 49}{space 3}0.000{col 57}{space 4} .1245282{col 70}{space 3} .3133545
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3555327{col 29}{space 2} .0412546{col 40}{space 1}    8.62{col 49}{space 3}0.000{col 57}{space 4} .2746715{col 70}{space 3} .4363939
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .0093895{col 29}{space 2} .0621558{col 40}{space 1}    0.15{col 49}{space 3}0.880{col 57}{space 4}-.1124389{col 70}{space 3}  .131218
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .5880949{col 29}{space 2} .0470739{col 40}{space 1}   12.49{col 49}{space 3}0.000{col 57}{space 4} .4958276{col 70}{space 3} .6803623
{txt}{space 10}2019  {c |}{col 17}{res}{space 2}  .302986{col 29}{space 2} .0466801{col 40}{space 1}    6.49{col 49}{space 3}0.000{col 57}{space 4} .2114907{col 70}{space 3} .3944814
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.509756{col 29}{space 2} .0804475{col 40}{space 1}   56.06{col 49}{space 3}0.000{col 57}{space 4} 4.352075{col 70}{space 3} 4.667437
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4721909
        {txt}sigma_e {c |} {res} 1.2322889
            {txt}rho {c |} {res} .58801287{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,410
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,555

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0324{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1014{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0881{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}15{txt},{res}4554{txt}){col 67}={col 70}{res}    14.77
{txt}corr(u_i, Xb){col 16}= {res}0.1024{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0610451{col 29}{space 2} .0111957{col 40}{space 1}    5.45{col 49}{space 3}0.000{col 57}{space 4} .0390961{col 70}{space 3} .0829941
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0558713{col 29}{space 2}  .013188{col 40}{space 1}    4.24{col 49}{space 3}0.000{col 57}{space 4} .0300164{col 70}{space 3} .0817262
{txt}dependent_share {c |}{col 17}{res}{space 2}-.1588592{col 29}{space 2} .0957348{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4}-.3465458{col 70}{space 3} .0288275
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0085877{col 29}{space 2}  .002933{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .0028377{col 70}{space 3} .0143377
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0152448{col 29}{space 2}  .085927{col 40}{space 1}   -0.18{col 49}{space 3}0.859{col 57}{space 4}-.1837033{col 70}{space 3} .1532137
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2062081{col 29}{space 2} .0478947{col 40}{space 1}    4.31{col 49}{space 3}0.000{col 57}{space 4} .1123114{col 70}{space 3} .3001049
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} -.210566{col 29}{space 2} .1560344{col 40}{space 1}   -1.35{col 49}{space 3}0.177{col 57}{space 4}-.5164692{col 70}{space 3} .0953372
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1682644{col 29}{space 2} .0377328{col 40}{space 1}    4.46{col 49}{space 3}0.000{col 57}{space 4} .0942899{col 70}{space 3}  .242239
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1139773{col 29}{space 2} .0460466{col 40}{space 1}    2.48{col 49}{space 3}0.013{col 57}{space 4} .0237037{col 70}{space 3}  .204251
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0899163{col 29}{space 2} .0630603{col 40}{space 1}    1.43{col 49}{space 3}0.154{col 57}{space 4}-.0337126{col 70}{space 3} .2135452
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}  .233742{col 29}{space 2} .0499048{col 40}{space 1}    4.68{col 49}{space 3}0.000{col 57}{space 4} .1359044{col 70}{space 3} .3315797
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0036421{col 29}{space 2} .0358477{col 40}{space 1}   -0.10{col 49}{space 3}0.919{col 57}{space 4} -.073921{col 70}{space 3} .0666367
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0089153{col 29}{space 2} .0043608{col 40}{space 1}    2.04{col 49}{space 3}0.041{col 57}{space 4} .0003659{col 70}{space 3} .0174646
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0011958{col 29}{space 2} .0467525{col 40}{space 1}    0.03{col 49}{space 3}0.980{col 57}{space 4}-.0904617{col 70}{space 3} .0928533
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.1691462{col 29}{space 2} .0229009{col 40}{space 1}   -7.39{col 49}{space 3}0.000{col 57}{space 4} -.214043{col 70}{space 3}-.1242493
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 3.225564{col 29}{space 2} .1533671{col 40}{space 1}   21.03{col 49}{space 3}0.000{col 57}{space 4}  2.92489{col 70}{space 3} 3.526238
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.224912
        {txt}sigma_e {c |} {res} 1.0763181
            {txt}rho {c |} {res} .56430342{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9   $xlist   $year_MALAWI if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     4,626
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     1,571

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0362{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2018{col 63}{txt}avg{col 67}={col 69}{res}       2.9
{txt}     overall = {res}0.1376{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}16{txt},{res}1570{txt}){col 67}={col 70}{res}     6.73
{txt}corr(u_i, Xb){col 16}= {res}0.2227{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1149195{col 29}{space 2} .0196013{col 40}{space 1}    5.86{col 49}{space 3}0.000{col 57}{space 4}  .076472{col 70}{space 3}  .153367
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0432258{col 29}{space 2} .0183834{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .0071672{col 70}{space 3} .0792844
{txt}dependent_share {c |}{col 17}{res}{space 2}-.2408083{col 29}{space 2} .1484479{col 40}{space 1}   -1.62{col 49}{space 3}0.105{col 57}{space 4}-.5319852{col 70}{space 3} .0503686
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0025112{col 29}{space 2} .0040175{col 40}{space 1}   -0.63{col 49}{space 3}0.532{col 57}{space 4}-.0103915{col 70}{space 3}  .005369
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1541247{col 29}{space 2} .0928138{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4}-.3361767{col 70}{space 3} .0279273
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1850164{col 29}{space 2} .0780404{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4}  .031942{col 70}{space 3} .3380908
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2482729{col 29}{space 2} .1895523{col 40}{space 1}    1.31{col 49}{space 3}0.190{col 57}{space 4}-.1235293{col 70}{space 3} .6200752
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .0766082{col 29}{space 2} .0697941{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4}-.0602913{col 70}{space 3} .2135076
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .182244{col 29}{space 2} .1382487{col 40}{space 1}    1.32{col 49}{space 3}0.188{col 57}{space 4}-.0889276{col 70}{space 3} .4534156
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1242269{col 29}{space 2} .0811277{col 40}{space 1}    1.53{col 49}{space 3}0.126{col 57}{space 4}-.0349032{col 70}{space 3} .2833571
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2262735{col 29}{space 2} .0561994{col 40}{space 1}    4.03{col 49}{space 3}0.000{col 57}{space 4} .1160397{col 70}{space 3} .3365073
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1140891{col 29}{space 2}  .049307{col 40}{space 1}   -2.31{col 49}{space 3}0.021{col 57}{space 4}-.2108036{col 70}{space 3}-.0173745
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0215683{col 29}{space 2} .0440503{col 40}{space 1}    0.49{col 49}{space 3}0.624{col 57}{space 4}-.0648353{col 70}{space 3} .1079719
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1041396{col 29}{space 2} .0756667{col 40}{space 1}    1.38{col 49}{space 3}0.169{col 57}{space 4}-.0442787{col 70}{space 3} .2525579
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .1863082{col 29}{space 2} .0616616{col 40}{space 1}    3.02{col 49}{space 3}0.003{col 57}{space 4} .0653604{col 70}{space 3} .3072559
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .0852512{col 29}{space 2} .0516926{col 40}{space 1}    1.65{col 49}{space 3}0.099{col 57}{space 4}-.0161426{col 70}{space 3} .1866451
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.332239{col 29}{space 2} .2428754{col 40}{space 1}   21.95{col 49}{space 3}0.000{col 57}{space 4} 4.855845{col 70}{space 3} 5.808634
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.360059
        {txt}sigma_e {c |} {res} 1.2834502
            {txt}rho {c |} {res} .52895565{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     6,536
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,837

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0501{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0082{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0169{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}15{txt},{res}3836{txt}){col 67}={col 70}{res}     8.73
{txt}corr(u_i, Xb){col 16}= {res}-0.1262{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .2476739{col 29}{space 2} .0355659{col 40}{space 1}    6.96{col 49}{space 3}0.000{col 57}{space 4}  .177944{col 70}{space 3} .3174039
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0494121{col 29}{space 2} .0184875{col 40}{space 1}   -2.67{col 49}{space 3}0.008{col 57}{space 4}-.0856584{col 70}{space 3}-.0131658
{txt}dependent_share {c |}{col 17}{res}{space 2} .2305667{col 29}{space 2} .2361999{col 40}{space 1}    0.98{col 49}{space 3}0.329{col 57}{space 4}-.2325228{col 70}{space 3} .6936562
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0068982{col 29}{space 2} .0056162{col 40}{space 1}    1.23{col 49}{space 3}0.219{col 57}{space 4} -.004113{col 70}{space 3} .0179093
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .2428621{col 29}{space 2} .1543033{col 40}{space 1}    1.57{col 49}{space 3}0.116{col 57}{space 4}-.0596623{col 70}{space 3} .5453865
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2113565{col 29}{space 2} .0867899{col 40}{space 1}    2.44{col 49}{space 3}0.015{col 57}{space 4} .0411978{col 70}{space 3} .3815152
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .3250947{col 29}{space 2} .1098872{col 40}{space 1}    2.96{col 49}{space 3}0.003{col 57}{space 4} .1096517{col 70}{space 3} .5405376
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1220714{col 29}{space 2} .0778819{col 40}{space 1}    1.57{col 49}{space 3}0.117{col 57}{space 4}-.0306226{col 70}{space 3} .2747653
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .320366{col 29}{space 2} .1218949{col 40}{space 1}    2.63{col 49}{space 3}0.009{col 57}{space 4} .0813809{col 70}{space 3} .5593511
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2050351{col 29}{space 2} .0897705{col 40}{space 1}    2.28{col 49}{space 3}0.022{col 57}{space 4} .0290326{col 70}{space 3} .3810375
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1633316{col 29}{space 2} .0679957{col 40}{space 1}   -2.40{col 49}{space 3}0.016{col 57}{space 4}-.2966428{col 70}{space 3}-.0300203
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0324363{col 29}{space 2} .0662997{col 40}{space 1}    0.49{col 49}{space 3}0.625{col 57}{space 4}-.0975498{col 70}{space 3} .1624224
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0054845{col 29}{space 2} .0026188{col 40}{space 1}    2.09{col 49}{space 3}0.036{col 57}{space 4} .0003502{col 70}{space 3} .0106188
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  .111484{col 29}{space 2} .3454404{col 40}{space 1}    0.32{col 49}{space 3}0.747{col 57}{space 4}-.5657805{col 70}{space 3} .7887484
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .3196624{col 29}{space 2} .0442818{col 40}{space 1}    7.22{col 49}{space 3}0.000{col 57}{space 4} .2328444{col 70}{space 3} .4064805
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.564612{col 29}{space 2} .3195211{col 40}{space 1}   14.29{col 49}{space 3}0.000{col 57}{space 4} 3.938165{col 70}{space 3}  5.19106
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4356237
        {txt}sigma_e {c |} {res} 1.3958609
            {txt}rho {c |} {res} .51404033{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    15,063
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     7,154

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0432{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1009{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.0848{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}7153{txt}){col 67}={col 70}{res}    18.72
{txt}corr(u_i, Xb){col 16}= {res}0.0960{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0714603{col 29}{space 2} .0155967{col 40}{space 1}    4.58{col 49}{space 3}0.000{col 57}{space 4} .0408861{col 70}{space 3} .1020344
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0239309{col 29}{space 2} .0098886{col 40}{space 1}    2.42{col 49}{space 3}0.016{col 57}{space 4} .0045463{col 70}{space 3} .0433155
{txt}dependent_share {c |}{col 17}{res}{space 2} .1840492{col 29}{space 2} .0885735{col 40}{space 1}    2.08{col 49}{space 3}0.038{col 57}{space 4}  .010419{col 70}{space 3} .3576794
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0027041{col 29}{space 2} .0023036{col 40}{space 1}   -1.17{col 49}{space 3}0.240{col 57}{space 4}-.0072198{col 70}{space 3} .0018116
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0050333{col 29}{space 2} .0822173{col 40}{space 1}   -0.06{col 49}{space 3}0.951{col 57}{space 4}-.1662036{col 70}{space 3} .1561371
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0320784{col 29}{space 2} .0395892{col 40}{space 1}    0.81{col 49}{space 3}0.418{col 57}{space 4}-.0455281{col 70}{space 3}  .109685
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.0008184{col 29}{space 2} .0417075{col 40}{space 1}   -0.02{col 49}{space 3}0.984{col 57}{space 4}-.0825774{col 70}{space 3} .0809406
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1481655{col 29}{space 2} .0404472{col 40}{space 1}    3.66{col 49}{space 3}0.000{col 57}{space 4} .0688771{col 70}{space 3}  .227454
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0877861{col 29}{space 2} .0491831{col 40}{space 1}    1.78{col 49}{space 3}0.074{col 57}{space 4}-.0086275{col 70}{space 3} .1841996
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}  .238692{col 29}{space 2} .0568147{col 40}{space 1}    4.20{col 49}{space 3}0.000{col 57}{space 4} .1273184{col 70}{space 3} .3500656
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2803767{col 29}{space 2}   .04314{col 40}{space 1}    6.50{col 49}{space 3}0.000{col 57}{space 4} .1958095{col 70}{space 3} .3649438
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0520358{col 29}{space 2} .0600849{col 40}{space 1}    0.87{col 49}{space 3}0.386{col 57}{space 4}-.0657484{col 70}{space 3} .1698201
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0045763{col 29}{space 2} .0111177{col 40}{space 1}    0.41{col 49}{space 3}0.681{col 57}{space 4}-.0172178{col 70}{space 3} .0263703
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}   .22151{col 29}{space 2} .1028622{col 40}{space 1}    2.15{col 49}{space 3}0.031{col 57}{space 4} .0198696{col 70}{space 3} .4231504
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.5911298{col 29}{space 2} .0527414{col 40}{space 1}  -11.21{col 49}{space 3}0.000{col 57}{space 4}-.6945185{col 70}{space 3}-.4877411
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.5198029{col 29}{space 2} .0509477{col 40}{space 1}  -10.20{col 49}{space 3}0.000{col 57}{space 4}-.6196755{col 70}{space 3}-.4199304
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.3381831{col 29}{space 2} .0499022{col 40}{space 1}   -6.78{col 49}{space 3}0.000{col 57}{space 4}-.4360061{col 70}{space 3}-.2403601
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.551009{col 29}{space 2} .1511053{col 40}{space 1}   36.74{col 49}{space 3}0.000{col 57}{space 4} 5.254798{col 70}{space 3}  5.84722
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4946316
        {txt}sigma_e {c |} {res} 1.2228102
            {txt}rho {c |} {res} .59903749{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,830
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,710

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0586{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0420{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.0568{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}17{txt},{res}5709{txt}){col 67}={col 70}{res}    21.64
{txt}corr(u_i, Xb){col 16}= {res}-0.0679{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .1931263{col 29}{space 2} .0137631{col 40}{space 1}   14.03{col 49}{space 3}0.000{col 57}{space 4} .1661453{col 70}{space 3} .2201072
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0155571{col 29}{space 2} .0109087{col 40}{space 1}    1.43{col 49}{space 3}0.154{col 57}{space 4}-.0058281{col 70}{space 3} .0369423
{txt}dependent_share {c |}{col 17}{res}{space 2}  .371672{col 29}{space 2} .1078523{col 40}{space 1}    3.45{col 49}{space 3}0.001{col 57}{space 4} .1602405{col 70}{space 3} .5831035
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0108231{col 29}{space 2} .0033776{col 40}{space 1}   -3.20{col 49}{space 3}0.001{col 57}{space 4}-.0174445{col 70}{space 3}-.0042018
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0642898{col 29}{space 2} .1005629{col 40}{space 1}    0.64{col 49}{space 3}0.523{col 57}{space 4}-.1328516{col 70}{space 3} .2614312
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0120845{col 29}{space 2} .0633439{col 40}{space 1}    0.19{col 49}{space 3}0.849{col 57}{space 4}-.1120936{col 70}{space 3} .1362626
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2494283{col 29}{space 2} .0850797{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .0826398{col 70}{space 3} .4162169
{txt}{space 10}phone {c |}{col 17}{res}{space 2}   .24246{col 29}{space 2}  .047899{col 40}{space 1}    5.06{col 49}{space 3}0.000{col 57}{space 4} .1485597{col 70}{space 3} .3363602
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1218493{col 29}{space 2} .0562162{col 40}{space 1}    2.17{col 49}{space 3}0.030{col 57}{space 4} .0116443{col 70}{space 3} .2320544
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0822057{col 29}{space 2} .0383805{col 40}{space 1}    2.14{col 49}{space 3}0.032{col 57}{space 4} .0069653{col 70}{space 3} .1574461
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .1941954{col 29}{space 2} .0400636{col 40}{space 1}    4.85{col 49}{space 3}0.000{col 57}{space 4} .1156556{col 70}{space 3} .2727351
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0404588{col 29}{space 2} .0439724{col 40}{space 1}   -0.92{col 49}{space 3}0.358{col 57}{space 4}-.1266615{col 70}{space 3} .0457439
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0105446{col 29}{space 2} .0062223{col 40}{space 1}    1.69{col 49}{space 3}0.090{col 57}{space 4}-.0016535{col 70}{space 3} .0227427
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}-.0898671{col 29}{space 2} .0492057{col 40}{space 1}   -1.83{col 49}{space 3}0.068{col 57}{space 4}-.1863289{col 70}{space 3} .0065947
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.1979711{col 29}{space 2} .0401154{col 40}{space 1}   -4.94{col 49}{space 3}0.000{col 57}{space 4}-.2766125{col 70}{space 3}-.1193298
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.1208403{col 29}{space 2} .0355165{col 40}{space 1}   -3.40{col 49}{space 3}0.001{col 57}{space 4}-.1904661{col 70}{space 3}-.0512145
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1325861{col 29}{space 2} .0426373{col 40}{space 1}    3.11{col 49}{space 3}0.002{col 57}{space 4} .0490008{col 70}{space 3} .2161714
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.036577{col 29}{space 2} .2002839{col 40}{space 1}   25.15{col 49}{space 3}0.000{col 57}{space 4} 4.643944{col 70}{space 3} 5.429209
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3634116
        {txt}sigma_e {c |} {res} 1.2092564
            {txt}rho {c |} {res} .55970599{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9   $xlist    $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    16,114
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,402

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0506{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1976{col 63}{txt}avg{col 67}={col 69}{res}       3.7
{txt}     overall = {res}0.1434{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}19{txt},{res}4401{txt}){col 67}={col 70}{res}    30.16
{txt}corr(u_i, Xb){col 16}= {res}0.1917{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}pdd9 {c |}{col 17}{res}{space 2} .0986703{col 29}{space 2} .0114344{col 40}{space 1}    8.63{col 49}{space 3}0.000{col 57}{space 4} .0762532{col 70}{space 3} .1210875
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0148749{col 29}{space 2} .0089066{col 40}{space 1}    1.67{col 49}{space 3}0.095{col 57}{space 4}-.0025865{col 70}{space 3} .0323363
{txt}dependent_share {c |}{col 17}{res}{space 2} .1035461{col 29}{space 2} .0815086{col 40}{space 1}    1.27{col 49}{space 3}0.204{col 57}{space 4}-.0562518{col 70}{space 3} .2633439
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0064514{col 29}{space 2} .0028129{col 40}{space 1}    2.29{col 49}{space 3}0.022{col 57}{space 4} .0009367{col 70}{space 3} .0119661
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0744792{col 29}{space 2} .0666176{col 40}{space 1}    1.12{col 49}{space 3}0.264{col 57}{space 4}-.0561248{col 70}{space 3} .2050832
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}   .19358{col 29}{space 2} .0472325{col 40}{space 1}    4.10{col 49}{space 3}0.000{col 57}{space 4} .1009806{col 70}{space 3} .2861794
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}  .233686{col 29}{space 2} .0562086{col 40}{space 1}    4.16{col 49}{space 3}0.000{col 57}{space 4} .1234888{col 70}{space 3} .3438832
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2463991{col 29}{space 2} .0376875{col 40}{space 1}    6.54{col 49}{space 3}0.000{col 57}{space 4} .1725126{col 70}{space 3} .3202857
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .3226445{col 29}{space 2} .0387007{col 40}{space 1}    8.34{col 49}{space 3}0.000{col 57}{space 4} .2467717{col 70}{space 3} .3985173
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0465806{col 29}{space 2} .0306772{col 40}{space 1}    1.52{col 49}{space 3}0.129{col 57}{space 4}-.0135622{col 70}{space 3} .1067234
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2003603{col 29}{space 2}  .032143{col 40}{space 1}    6.23{col 49}{space 3}0.000{col 57}{space 4} .1373439{col 70}{space 3} .2633767
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0349754{col 29}{space 2} .0278743{col 40}{space 1}    1.25{col 49}{space 3}0.210{col 57}{space 4}-.0196722{col 70}{space 3} .0896231
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}-.0003789{col 29}{space 2} .0015063{col 40}{space 1}   -0.25{col 49}{space 3}0.801{col 57}{space 4} -.003332{col 70}{space 3} .0025743
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0222514{col 29}{space 2} .0368314{col 40}{space 1}    0.60{col 49}{space 3}0.546{col 57}{space 4}-.0499566{col 70}{space 3} .0944594
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1221531{col 29}{space 2} .0402862{col 40}{space 1}   -3.03{col 49}{space 3}0.002{col 57}{space 4}-.2011343{col 70}{space 3}-.0431718
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0229643{col 29}{space 2} .0360037{col 40}{space 1}   -0.64{col 49}{space 3}0.524{col 57}{space 4}-.0935497{col 70}{space 3} .0476212
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .3359048{col 29}{space 2} .0354925{col 40}{space 1}    9.46{col 49}{space 3}0.000{col 57}{space 4} .2663217{col 70}{space 3}  .405488
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0787289{col 29}{space 2} .0351153{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} .0098853{col 70}{space 3} .1475726
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2811571{col 29}{space 2} .0330855{col 40}{space 1}    8.50{col 49}{space 3}0.000{col 57}{space 4} .2162928{col 70}{space 3} .3460214
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.190152{col 29}{space 2}  .166301{col 40}{space 1}   25.20{col 49}{space 3}0.000{col 57}{space 4} 3.864119{col 70}{space 3} 4.516186
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2224056
        {txt}sigma_e {c |} {res} 1.2635858
            {txt}rho {c |} {res} .48343965{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. 
. 
. esttab using  S24_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S24_fe.rtf not found)
(output written to {browse  `"S24_fe.rtf"'})

{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                  S25                                         *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_vill sum_vill  $xlist   i.year    , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    65,579
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    27,229

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0284{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1509{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.1107{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}25{txt},{res}27228{txt}){col 67}={col 70}{res}    40.68
{txt}corr(u_i, Xb){col 16}= {res}0.1924{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .0276454{col 29}{space 2}  .007245{col 40}{space 1}    3.82{col 49}{space 3}0.000{col 57}{space 4} .0134448{col 70}{space 3} .0418459
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2} .0006569{col 29}{space 2} .0048112{col 40}{space 1}    0.14{col 49}{space 3}0.891{col 57}{space 4}-.0087733{col 70}{space 3} .0100871
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}  .029736{col 29}{space 2} .0049583{col 40}{space 1}    6.00{col 49}{space 3}0.000{col 57}{space 4} .0200176{col 70}{space 3} .0394545
{txt}dependent_share {c |}{col 17}{res}{space 2} .1107707{col 29}{space 2} .0440454{col 40}{space 1}    2.51{col 49}{space 3}0.012{col 57}{space 4} .0244395{col 70}{space 3}  .197102
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0022676{col 29}{space 2} .0013506{col 40}{space 1}   -1.68{col 49}{space 3}0.093{col 57}{space 4}-.0049148{col 70}{space 3} .0003795
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} -.056092{col 29}{space 2} .0372985{col 40}{space 1}   -1.50{col 49}{space 3}0.133{col 57}{space 4} -.129199{col 70}{space 3} .0170151
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1220654{col 29}{space 2} .0225475{col 40}{space 1}    5.41{col 49}{space 3}0.000{col 57}{space 4} .0778712{col 70}{space 3} .1662596
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1168877{col 29}{space 2} .0293912{col 40}{space 1}    3.98{col 49}{space 3}0.000{col 57}{space 4} .0592794{col 70}{space 3}  .174496
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1549185{col 29}{space 2} .0194638{col 40}{space 1}    7.96{col 49}{space 3}0.000{col 57}{space 4} .1167684{col 70}{space 3} .1930685
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1337909{col 29}{space 2} .0230041{col 40}{space 1}    5.82{col 49}{space 3}0.000{col 57}{space 4} .0887016{col 70}{space 3} .1788802
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1219429{col 29}{space 2} .0199282{col 40}{space 1}    6.12{col 49}{space 3}0.000{col 57}{space 4} .0828826{col 70}{space 3} .1610032
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2131473{col 29}{space 2} .0183056{col 40}{space 1}   11.64{col 49}{space 3}0.000{col 57}{space 4} .1772673{col 70}{space 3} .2490272
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0544249{col 29}{space 2} .0173312{col 40}{space 1}    3.14{col 49}{space 3}0.002{col 57}{space 4} .0204549{col 70}{space 3}  .088395
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .005019{col 29}{space 2} .0017697{col 40}{space 1}    2.84{col 49}{space 3}0.005{col 57}{space 4} .0015504{col 70}{space 3} .0084877
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0632411{col 29}{space 2} .0232899{col 40}{space 1}    2.72{col 49}{space 3}0.007{col 57}{space 4} .0175917{col 70}{space 3} .1088905
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1569131{col 29}{space 2}   .04972{col 40}{space 1}   -3.16{col 49}{space 3}0.002{col 57}{space 4}-.2543668{col 70}{space 3}-.0594594
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .0941618{col 29}{space 2} .0368642{col 40}{space 1}    2.55{col 49}{space 3}0.011{col 57}{space 4} .0219061{col 70}{space 3} .1664176
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2157733{col 29}{space 2} .0426917{col 40}{space 1}    5.05{col 49}{space 3}0.000{col 57}{space 4} .1320953{col 70}{space 3} .2994512
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0926666{col 29}{space 2} .0378616{col 40}{space 1}    2.45{col 49}{space 3}0.014{col 57}{space 4} .0184559{col 70}{space 3} .1668773
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2688859{col 29}{space 2} .0429138{col 40}{space 1}    6.27{col 49}{space 3}0.000{col 57}{space 4} .1847726{col 70}{space 3} .3529992
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .1767244{col 29}{space 2}  .048457{col 40}{space 1}    3.65{col 49}{space 3}0.000{col 57}{space 4} .0817462{col 70}{space 3} .2717026
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3315853{col 29}{space 2} .0415434{col 40}{space 1}    7.98{col 49}{space 3}0.000{col 57}{space 4} .2501582{col 70}{space 3} .4130124
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0349006{col 29}{space 2} .0622326{col 40}{space 1}   -0.56{col 49}{space 3}0.575{col 57}{space 4}-.1568796{col 70}{space 3} .0870784
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .5442654{col 29}{space 2} .0472945{col 40}{space 1}   11.51{col 49}{space 3}0.000{col 57}{space 4} .4515657{col 70}{space 3}  .636965
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .2715136{col 29}{space 2} .0469771{col 40}{space 1}    5.78{col 49}{space 3}0.000{col 57}{space 4} .1794361{col 70}{space 3}  .363591
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}  4.60504{col 29}{space 2} .0931294{col 40}{space 1}   49.45{col 49}{space 3}0.000{col 57}{space 4} 4.422502{col 70}{space 3} 4.787579
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4510653
        {txt}sigma_e {c |} {res} 1.2371012
            {txt}rho {c |} {res} .57909374{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,410
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,555

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0298{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0678{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0725{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}16{txt},{res}4554{txt}){col 67}={col 70}{res}    12.80
{txt}corr(u_i, Xb){col 16}= {res}0.0740{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .0386402{col 29}{space 2}  .015286{col 40}{space 1}    2.53{col 49}{space 3}0.012{col 57}{space 4} .0086722{col 70}{space 3} .0686082
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2} .0242672{col 29}{space 2} .0131853{col 40}{space 1}    1.84{col 49}{space 3}0.066{col 57}{space 4}-.0015824{col 70}{space 3} .0501168
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0595459{col 29}{space 2} .0132169{col 40}{space 1}    4.51{col 49}{space 3}0.000{col 57}{space 4} .0336344{col 70}{space 3} .0854574
{txt}dependent_share {c |}{col 17}{res}{space 2}-.1630353{col 29}{space 2} .0960291{col 40}{space 1}   -1.70{col 49}{space 3}0.090{col 57}{space 4}-.3512989{col 70}{space 3} .0252283
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0094864{col 29}{space 2}  .002928{col 40}{space 1}    3.24{col 49}{space 3}0.001{col 57}{space 4} .0037461{col 70}{space 3} .0152266
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}  -.01686{col 29}{space 2} .0859419{col 40}{space 1}   -0.20{col 49}{space 3}0.844{col 57}{space 4}-.1853478{col 70}{space 3} .1516278
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2152587{col 29}{space 2} .0481679{col 40}{space 1}    4.47{col 49}{space 3}0.000{col 57}{space 4} .1208263{col 70}{space 3} .3096912
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1949718{col 29}{space 2} .1549076{col 40}{space 1}   -1.26{col 49}{space 3}0.208{col 57}{space 4}-.4986657{col 70}{space 3} .1087222
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1730166{col 29}{space 2} .0378148{col 40}{space 1}    4.58{col 49}{space 3}0.000{col 57}{space 4} .0988813{col 70}{space 3} .2471519
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1184621{col 29}{space 2} .0460022{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0282755{col 70}{space 3} .2086486
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0859562{col 29}{space 2}  .063223{col 40}{space 1}    1.36{col 49}{space 3}0.174{col 57}{space 4}-.0379914{col 70}{space 3} .2099039
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2324981{col 29}{space 2} .0500135{col 40}{space 1}    4.65{col 49}{space 3}0.000{col 57}{space 4} .1344474{col 70}{space 3} .3305488
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0044313{col 29}{space 2} .0359383{col 40}{space 1}   -0.12{col 49}{space 3}0.902{col 57}{space 4}-.0748877{col 70}{space 3} .0660251
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0104061{col 29}{space 2} .0044407{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 57}{space 4} .0017001{col 70}{space 3}  .019112
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0334052{col 29}{space 2} .0466128{col 40}{space 1}    0.72{col 49}{space 3}0.474{col 57}{space 4}-.0579786{col 70}{space 3}  .124789
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.1653619{col 29}{space 2} .0229559{col 40}{space 1}   -7.20{col 49}{space 3}0.000{col 57}{space 4}-.2103666{col 70}{space 3}-.1203573
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.876535{col 29}{space 2} .1976908{col 40}{space 1}   14.55{col 49}{space 3}0.000{col 57}{space 4} 2.488965{col 70}{space 3} 3.264105
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2423998
        {txt}sigma_e {c |} {res} 1.0778015
            {txt}rho {c |} {res} .57058614{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_MALAWI  if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     4,626
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     1,571

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0280{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1188{col 63}{txt}avg{col 67}={col 69}{res}       2.9
{txt}     overall = {res}0.0854{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}1570{txt}){col 67}={col 70}{res}     4.59
{txt}corr(u_i, Xb){col 16}= {res}0.1361{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .0580452{col 29}{space 2} .0257673{col 40}{space 1}    2.25{col 49}{space 3}0.024{col 57}{space 4} .0075033{col 70}{space 3} .1085871
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2} .0232815{col 29}{space 2} .0188518{col 40}{space 1}    1.23{col 49}{space 3}0.217{col 57}{space 4}-.0136959{col 70}{space 3} .0602589
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0496061{col 29}{space 2} .0184869{col 40}{space 1}    2.68{col 49}{space 3}0.007{col 57}{space 4} .0133445{col 70}{space 3} .0858676
{txt}dependent_share {c |}{col 17}{res}{space 2} -.246169{col 29}{space 2}  .148514{col 40}{space 1}   -1.66{col 49}{space 3}0.098{col 57}{space 4}-.5374757{col 70}{space 3} .0451377
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0018246{col 29}{space 2} .0040736{col 40}{space 1}   -0.45{col 49}{space 3}0.654{col 57}{space 4}-.0098148{col 70}{space 3} .0061656
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1546465{col 29}{space 2} .0937536{col 40}{space 1}   -1.65{col 49}{space 3}0.099{col 57}{space 4}-.3385419{col 70}{space 3} .0292489
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1965092{col 29}{space 2} .0783834{col 40}{space 1}    2.51{col 49}{space 3}0.012{col 57}{space 4}  .042762{col 70}{space 3} .3502564
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2407116{col 29}{space 2} .1922633{col 40}{space 1}    1.25{col 49}{space 3}0.211{col 57}{space 4}-.1364082{col 70}{space 3} .6178314
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .085592{col 29}{space 2} .0700387{col 40}{space 1}    1.22{col 49}{space 3}0.222{col 57}{space 4}-.0517874{col 70}{space 3} .2229713
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1570358{col 29}{space 2} .1402005{col 40}{space 1}    1.12{col 49}{space 3}0.263{col 57}{space 4}-.1179642{col 70}{space 3} .4320358
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1115608{col 29}{space 2} .0818287{col 40}{space 1}    1.36{col 49}{space 3}0.173{col 57}{space 4}-.0489442{col 70}{space 3} .2720658
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2428262{col 29}{space 2} .0565253{col 40}{space 1}    4.30{col 49}{space 3}0.000{col 57}{space 4} .1319532{col 70}{space 3} .3536993
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1287691{col 29}{space 2} .0495457{col 40}{space 1}   -2.60{col 49}{space 3}0.009{col 57}{space 4}-.2259518{col 70}{space 3}-.0315864
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0585642{col 29}{space 2} .0473845{col 40}{space 1}    1.24{col 49}{space 3}0.217{col 57}{space 4}-.0343793{col 70}{space 3} .1515077
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1402742{col 29}{space 2} .0761082{col 40}{space 1}    1.84{col 49}{space 3}0.066{col 57}{space 4}-.0090102{col 70}{space 3} .2895586
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .0950996{col 29}{space 2} .0826915{col 40}{space 1}    1.15{col 49}{space 3}0.250{col 57}{space 4}-.0670978{col 70}{space 3} .2572969
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .0682575{col 29}{space 2} .0531914{col 40}{space 1}    1.28{col 49}{space 3}0.200{col 57}{space 4}-.0360762{col 70}{space 3} .1725912
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.974978{col 29}{space 2} .3405216{col 40}{space 1}   14.61{col 49}{space 3}0.000{col 57}{space 4} 4.307053{col 70}{space 3} 5.642903
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3969557
        {txt}sigma_e {c |} {res} 1.2890757
            {txt}rho {c |} {res} .54009866{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     6,536
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,837

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0366{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0138{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0196{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}16{txt},{res}3836{txt}){col 67}={col 70}{res}     6.05
{txt}corr(u_i, Xb){col 16}= {res}-0.0786{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .1046513{col 29}{space 2} .0313023{col 40}{space 1}    3.34{col 49}{space 3}0.001{col 57}{space 4} .0432805{col 70}{space 3} .1660221
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2} .0119625{col 29}{space 2} .0197071{col 40}{space 1}    0.61{col 49}{space 3}0.544{col 57}{space 4}-.0266749{col 70}{space 3}    .0506
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0422283{col 29}{space 2} .0185636{col 40}{space 1}   -2.27{col 49}{space 3}0.023{col 57}{space 4}-.0786238{col 70}{space 3}-.0058328
{txt}dependent_share {c |}{col 17}{res}{space 2} .2353066{col 29}{space 2} .2377291{col 40}{space 1}    0.99{col 49}{space 3}0.322{col 57}{space 4} -.230781{col 70}{space 3} .7013941
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0077742{col 29}{space 2} .0056419{col 40}{space 1}    1.38{col 49}{space 3}0.168{col 57}{space 4}-.0032872{col 70}{space 3} .0188356
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .1814038{col 29}{space 2}  .153903{col 40}{space 1}    1.18{col 49}{space 3}0.239{col 57}{space 4}-.1203357{col 70}{space 3} .4831433
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2051732{col 29}{space 2} .0876395{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 57}{space 4} .0333487{col 70}{space 3} .3769976
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .3558278{col 29}{space 2} .1108028{col 40}{space 1}    3.21{col 49}{space 3}0.001{col 57}{space 4} .1385898{col 70}{space 3} .5730658
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1376822{col 29}{space 2} .0784758{col 40}{space 1}    1.75{col 49}{space 3}0.079{col 57}{space 4}-.0161761{col 70}{space 3} .2915406
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2869052{col 29}{space 2} .1243561{col 40}{space 1}    2.31{col 49}{space 3}0.021{col 57}{space 4} .0430949{col 70}{space 3} .5307155
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2210351{col 29}{space 2} .0904712{col 40}{space 1}    2.44{col 49}{space 3}0.015{col 57}{space 4} .0436589{col 70}{space 3} .3984114
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1524704{col 29}{space 2} .0690884{col 40}{space 1}   -2.21{col 49}{space 3}0.027{col 57}{space 4}-.2879239{col 70}{space 3}-.0170169
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0436465{col 29}{space 2} .0672889{col 40}{space 1}    0.65{col 49}{space 3}0.517{col 57}{space 4}-.0882788{col 70}{space 3} .1755719
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0060957{col 29}{space 2} .0026023{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 57}{space 4} .0009938{col 70}{space 3} .0111977
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1705947{col 29}{space 2} .3485313{col 40}{space 1}    0.49{col 49}{space 3}0.625{col 57}{space 4}-.5127296{col 70}{space 3} .8539191
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .2842683{col 29}{space 2} .0476281{col 40}{space 1}    5.97{col 49}{space 3}0.000{col 57}{space 4} .1908896{col 70}{space 3}  .377647
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.383265{col 29}{space 2} .4131786{col 40}{space 1}   10.61{col 49}{space 3}0.000{col 57}{space 4} 3.573195{col 70}{space 3} 5.193336
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4219711
        {txt}sigma_e {c |} {res} 1.4060479
            {txt}rho {c |} {res} .50563032{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    15,063
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     7,154

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0422{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1623{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.1309{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}18{txt},{res}7153{txt}){col 67}={col 70}{res}    17.56
{txt}corr(u_i, Xb){col 16}= {res}0.1783{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .0527002{col 29}{space 2} .0160243{col 40}{space 1}    3.29{col 49}{space 3}0.001{col 57}{space 4} .0212878{col 70}{space 3} .0841126
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2}-.0313268{col 29}{space 2} .0131527{col 40}{space 1}   -2.38{col 49}{space 3}0.017{col 57}{space 4}-.0571099{col 70}{space 3}-.0055436
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0288809{col 29}{space 2}   .00987{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .0095328{col 70}{space 3}  .048229
{txt}dependent_share {c |}{col 17}{res}{space 2} .1700351{col 29}{space 2} .0886275{col 40}{space 1}    1.92{col 49}{space 3}0.055{col 57}{space 4}-.0037011{col 70}{space 3} .3437712
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0026835{col 29}{space 2} .0022977{col 40}{space 1}   -1.17{col 49}{space 3}0.243{col 57}{space 4}-.0071878{col 70}{space 3} .0018207
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0105878{col 29}{space 2} .0819516{col 40}{space 1}   -0.13{col 49}{space 3}0.897{col 57}{space 4}-.1712372{col 70}{space 3} .1500616
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0350744{col 29}{space 2} .0395969{col 40}{space 1}    0.89{col 49}{space 3}0.376{col 57}{space 4}-.0425471{col 70}{space 3}  .112696
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0036346{col 29}{space 2} .0416816{col 40}{space 1}    0.09{col 49}{space 3}0.931{col 57}{space 4}-.0780736{col 70}{space 3} .0853429
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1513075{col 29}{space 2} .0404851{col 40}{space 1}    3.74{col 49}{space 3}0.000{col 57}{space 4} .0719447{col 70}{space 3} .2306703
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .083274{col 29}{space 2} .0491747{col 40}{space 1}    1.69{col 49}{space 3}0.090{col 57}{space 4}-.0131229{col 70}{space 3}  .179671
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2280739{col 29}{space 2} .0568671{col 40}{space 1}    4.01{col 49}{space 3}0.000{col 57}{space 4} .1165976{col 70}{space 3} .3395503
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2806659{col 29}{space 2} .0431728{col 40}{space 1}    6.50{col 49}{space 3}0.000{col 57}{space 4} .1960344{col 70}{space 3} .3652974
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0526343{col 29}{space 2} .0600087{col 40}{space 1}    0.88{col 49}{space 3}0.380{col 57}{space 4}-.0650005{col 70}{space 3} .1702691
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0083413{col 29}{space 2} .0113704{col 40}{space 1}    0.73{col 49}{space 3}0.463{col 57}{space 4} -.013948{col 70}{space 3} .0306306
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .2380865{col 29}{space 2} .1026472{col 40}{space 1}    2.32{col 49}{space 3}0.020{col 57}{space 4} .0368676{col 70}{space 3} .4393053
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} -.576703{col 29}{space 2} .0529985{col 40}{space 1}  -10.88{col 49}{space 3}0.000{col 57}{space 4}-.6805958{col 70}{space 3}-.4728102
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.5120522{col 29}{space 2} .0519182{col 40}{space 1}   -9.86{col 49}{space 3}0.000{col 57}{space 4}-.6138273{col 70}{space 3}-.4102771
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.3376681{col 29}{space 2} .0513016{col 40}{space 1}   -6.58{col 49}{space 3}0.000{col 57}{space 4}-.4382345{col 70}{space 3}-.2371018
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.692072{col 29}{space 2} .1924251{col 40}{space 1}   29.58{col 49}{space 3}0.000{col 57}{space 4} 5.314862{col 70}{space 3} 6.069282
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4609039
        {txt}sigma_e {c |} {res} 1.2234985
            {txt}rho {c |} {res} .58775248{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,830
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,710

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0294{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0949{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.0772{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}18{txt},{res}5709{txt}){col 67}={col 70}{res}     9.82
{txt}corr(u_i, Xb){col 16}= {res}0.0616{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2} .0370959{col 29}{space 2} .0190944{col 40}{space 1}    1.94{col 49}{space 3}0.052{col 57}{space 4}-.0003363{col 70}{space 3}  .074528
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2}-.0044384{col 29}{space 2} .0129517{col 40}{space 1}   -0.34{col 49}{space 3}0.732{col 57}{space 4}-.0298286{col 70}{space 3} .0209519
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0287576{col 29}{space 2} .0110269{col 40}{space 1}    2.61{col 49}{space 3}0.009{col 57}{space 4} .0071407{col 70}{space 3} .0503745
{txt}dependent_share {c |}{col 17}{res}{space 2} .3814443{col 29}{space 2} .1094238{col 40}{space 1}    3.49{col 49}{space 3}0.000{col 57}{space 4}  .166932{col 70}{space 3} .5959565
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} -.009696{col 29}{space 2} .0035864{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4}-.0167268{col 70}{space 3}-.0026652
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}  .015089{col 29}{space 2} .1047917{col 40}{space 1}    0.14{col 49}{space 3}0.886{col 57}{space 4}-.1903425{col 70}{space 3} .2205205
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0066381{col 29}{space 2} .0646849{col 40}{space 1}    0.10{col 49}{space 3}0.918{col 57}{space 4}-.1201689{col 70}{space 3} .1334451
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2592245{col 29}{space 2} .0865742{col 40}{space 1}    2.99{col 49}{space 3}0.003{col 57}{space 4} .0895063{col 70}{space 3} .4289427
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2681145{col 29}{space 2} .0487998{col 40}{space 1}    5.49{col 49}{space 3}0.000{col 57}{space 4} .1724482{col 70}{space 3} .3637807
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1070234{col 29}{space 2} .0574188{col 40}{space 1}    1.86{col 49}{space 3}0.062{col 57}{space 4}-.0055393{col 70}{space 3} .2195861
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1036683{col 29}{space 2} .0388496{col 40}{space 1}    2.67{col 49}{space 3}0.008{col 57}{space 4} .0275082{col 70}{space 3} .1798283
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2168028{col 29}{space 2} .0404109{col 40}{space 1}    5.36{col 49}{space 3}0.000{col 57}{space 4} .1375821{col 70}{space 3} .2960234
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0305831{col 29}{space 2} .0446398{col 40}{space 1}   -0.69{col 49}{space 3}0.493{col 57}{space 4} -.118094{col 70}{space 3} .0569278
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0155367{col 29}{space 2} .0069773{col 40}{space 1}    2.23{col 49}{space 3}0.026{col 57}{space 4} .0018586{col 70}{space 3} .0292148
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0076108{col 29}{space 2} .0497378{col 40}{space 1}    0.15{col 49}{space 3}0.878{col 57}{space 4}-.0898942{col 70}{space 3} .1051158
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.1469801{col 29}{space 2} .0407868{col 40}{space 1}   -3.60{col 49}{space 3}0.000{col 57}{space 4}-.2269377{col 70}{space 3}-.0670226
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.1339445{col 29}{space 2} .0361393{col 40}{space 1}   -3.71{col 49}{space 3}0.000{col 57}{space 4}-.2047913{col 70}{space 3}-.0630978
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1349782{col 29}{space 2} .0455112{col 40}{space 1}    2.97{col 49}{space 3}0.003{col 57}{space 4} .0457589{col 70}{space 3} .2241975
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.287661{col 29}{space 2} .2335006{col 40}{space 1}   22.65{col 49}{space 3}0.000{col 57}{space 4} 4.829911{col 70}{space 3} 5.745411
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.321412
        {txt}sigma_e {c |} {res} 1.2279711
            {txt}rho {c |} {res}  .5366032{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_vill sum_vill  $xlist   $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    16,114
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,402

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0444{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2223{col 63}{txt}avg{col 67}={col 69}{res}       3.7
{txt}     overall = {res}0.1459{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}20{txt},{res}4401{txt}){col 67}={col 70}{res}    25.31
{txt}corr(u_i, Xb){col 16}= {res}0.2165{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_vill {c |}{col 17}{res}{space 2}  .007865{col 29}{space 2} .0135895{col 40}{space 1}    0.58{col 49}{space 3}0.563{col 57}{space 4}-.0187772{col 70}{space 3} .0345072
{txt}{space 7}sum_vill {c |}{col 17}{res}{space 2}-.0126372{col 29}{space 2} .0073398{col 40}{space 1}   -1.72{col 49}{space 3}0.085{col 57}{space 4}-.0270269{col 70}{space 3} .0017526
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0215028{col 29}{space 2} .0089865{col 40}{space 1}    2.39{col 49}{space 3}0.017{col 57}{space 4} .0038846{col 70}{space 3} .0391209
{txt}dependent_share {c |}{col 17}{res}{space 2} .1111346{col 29}{space 2} .0823197{col 40}{space 1}    1.35{col 49}{space 3}0.177{col 57}{space 4}-.0502535{col 70}{space 3} .2725227
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0066018{col 29}{space 2} .0028324{col 40}{space 1}    2.33{col 49}{space 3}0.020{col 57}{space 4} .0010489{col 70}{space 3} .0121546
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0622123{col 29}{space 2} .0673086{col 40}{space 1}    0.92{col 49}{space 3}0.355{col 57}{space 4}-.0697465{col 70}{space 3} .1941711
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2008452{col 29}{space 2} .0476198{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .1074863{col 70}{space 3}  .294204
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2439195{col 29}{space 2} .0563636{col 40}{space 1}    4.33{col 49}{space 3}0.000{col 57}{space 4} .1334185{col 70}{space 3} .3544204
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2535436{col 29}{space 2} .0378402{col 40}{space 1}    6.70{col 49}{space 3}0.000{col 57}{space 4} .1793578{col 70}{space 3} .3277294
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .326371{col 29}{space 2} .0387758{col 40}{space 1}    8.42{col 49}{space 3}0.000{col 57}{space 4}  .250351{col 70}{space 3}  .402391
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}  .046371{col 29}{space 2}   .03083{col 40}{space 1}    1.50{col 49}{space 3}0.133{col 57}{space 4}-.0140713{col 70}{space 3} .1068133
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2117431{col 29}{space 2} .0322196{col 40}{space 1}    6.57{col 49}{space 3}0.000{col 57}{space 4} .1485765{col 70}{space 3} .2749097
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0465007{col 29}{space 2}  .027935{col 40}{space 1}    1.66{col 49}{space 3}0.096{col 57}{space 4} -.008266{col 70}{space 3} .1012675
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0006016{col 29}{space 2} .0015716{col 40}{space 1}    0.38{col 49}{space 3}0.702{col 57}{space 4}-.0024795{col 70}{space 3} .0036827
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  .060942{col 29}{space 2} .0369492{col 40}{space 1}    1.65{col 49}{space 3}0.099{col 57}{space 4}-.0114969{col 70}{space 3} .1333809
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1130945{col 29}{space 2} .0408281{col 40}{space 1}   -2.77{col 49}{space 3}0.006{col 57}{space 4} -.193138{col 70}{space 3}-.0330509
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0031659{col 29}{space 2} .0371321{col 40}{space 1}   -0.09{col 49}{space 3}0.932{col 57}{space 4}-.0759635{col 70}{space 3} .0696317
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .3549029{col 29}{space 2} .0361791{col 40}{space 1}    9.81{col 49}{space 3}0.000{col 57}{space 4} .2839737{col 70}{space 3}  .425832
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0927285{col 29}{space 2} .0354524{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4}  .023224{col 70}{space 3}  .162233
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2704162{col 29}{space 2} .0331282{col 40}{space 1}    8.16{col 49}{space 3}0.000{col 57}{space 4} .2054682{col 70}{space 3} .3353642
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.491945{col 29}{space 2}  .183518{col 40}{space 1}   24.48{col 49}{space 3}0.000{col 57}{space 4} 4.132157{col 70}{space 3} 4.851733
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2164413
        {txt}sigma_e {c |} {res} 1.2677833
            {txt}rho {c |} {res} .47934162{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S25_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S25_fe.rtf not found)
(output written to {browse  `"S25_fe.rtf"'})

{com}. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                  S26                                         *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_town sum_town  $xlist   i.year   , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    65,579
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    27,229

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0284{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1192{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.0974{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}25{txt},{res}27228{txt}){col 67}={col 70}{res}    40.71
{txt}corr(u_i, Xb){col 16}= {res}0.1336{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2} .0258839{col 29}{space 2}  .007435{col 40}{space 1}    3.48{col 49}{space 3}0.000{col 57}{space 4} .0113109{col 70}{space 3} .0404569
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}-.0050705{col 29}{space 2} .0019527{col 40}{space 1}   -2.60{col 49}{space 3}0.009{col 57}{space 4} -.008898{col 70}{space 3}-.0012431
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0297795{col 29}{space 2} .0049558{col 40}{space 1}    6.01{col 49}{space 3}0.000{col 57}{space 4} .0200659{col 70}{space 3} .0394931
{txt}dependent_share {c |}{col 17}{res}{space 2} .1121149{col 29}{space 2} .0440364{col 40}{space 1}    2.55{col 49}{space 3}0.011{col 57}{space 4} .0258014{col 70}{space 3} .1984285
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0023243{col 29}{space 2} .0013501{col 40}{space 1}   -1.72{col 49}{space 3}0.085{col 57}{space 4}-.0049705{col 70}{space 3} .0003219
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0557865{col 29}{space 2} .0373038{col 40}{space 1}   -1.50{col 49}{space 3}0.135{col 57}{space 4}-.1289038{col 70}{space 3} .0173309
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1209464{col 29}{space 2} .0225478{col 40}{space 1}    5.36{col 49}{space 3}0.000{col 57}{space 4} .0767516{col 70}{space 3} .1651413
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1152686{col 29}{space 2} .0293708{col 40}{space 1}    3.92{col 49}{space 3}0.000{col 57}{space 4} .0577003{col 70}{space 3} .1728369
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .155247{col 29}{space 2}  .019455{col 40}{space 1}    7.98{col 49}{space 3}0.000{col 57}{space 4} .1171141{col 70}{space 3} .1933798
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1332002{col 29}{space 2} .0230149{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 57}{space 4} .0880899{col 70}{space 3} .1783105
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1225054{col 29}{space 2} .0199194{col 40}{space 1}    6.15{col 49}{space 3}0.000{col 57}{space 4} .0834623{col 70}{space 3} .1615485
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2134089{col 29}{space 2}  .018301{col 40}{space 1}   11.66{col 49}{space 3}0.000{col 57}{space 4}  .177538{col 70}{space 3} .2492798
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0548134{col 29}{space 2} .0173391{col 40}{space 1}    3.16{col 49}{space 3}0.002{col 57}{space 4} .0208279{col 70}{space 3} .0887989
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0050953{col 29}{space 2} .0017791{col 40}{space 1}    2.86{col 49}{space 3}0.004{col 57}{space 4} .0016081{col 70}{space 3} .0085824
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0656909{col 29}{space 2} .0232856{col 40}{space 1}    2.82{col 49}{space 3}0.005{col 57}{space 4}   .02005{col 70}{space 3} .1113318
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1533799{col 29}{space 2} .0497596{col 40}{space 1}   -3.08{col 49}{space 3}0.002{col 57}{space 4}-.2509112{col 70}{space 3}-.0558486
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .1030123{col 29}{space 2}  .036842{col 40}{space 1}    2.80{col 49}{space 3}0.005{col 57}{space 4} .0308001{col 70}{space 3} .1752245
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2269062{col 29}{space 2} .0429293{col 40}{space 1}    5.29{col 49}{space 3}0.000{col 57}{space 4} .1427626{col 70}{space 3} .3110497
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1006413{col 29}{space 2} .0379284{col 40}{space 1}    2.65{col 49}{space 3}0.008{col 57}{space 4} .0262998{col 70}{space 3} .1749829
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2791729{col 29}{space 2} .0431368{col 40}{space 1}    6.47{col 49}{space 3}0.000{col 57}{space 4} .1946226{col 70}{space 3} .3637232
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .1568058{col 29}{space 2} .0491165{col 40}{space 1}    3.19{col 49}{space 3}0.001{col 57}{space 4} .0605349{col 70}{space 3} .2530767
{txt}{space 10}2015  {c |}{col 17}{res}{space 2} .3406632{col 29}{space 2} .0417516{col 40}{space 1}    8.16{col 49}{space 3}0.000{col 57}{space 4} .2588279{col 70}{space 3} .4224985
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0417792{col 29}{space 2} .0621891{col 40}{space 1}   -0.67{col 49}{space 3}0.502{col 57}{space 4} -.163673{col 70}{space 3} .0801146
{txt}{space 10}2018  {c |}{col 17}{res}{space 2} .5541227{col 29}{space 2} .0475501{col 40}{space 1}   11.65{col 49}{space 3}0.000{col 57}{space 4} .4609222{col 70}{space 3} .6473233
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .2664794{col 29}{space 2} .0469927{col 40}{space 1}    5.67{col 49}{space 3}0.000{col 57}{space 4} .1743712{col 70}{space 3} .3585875
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.695144{col 29}{space 2} .0926993{col 40}{space 1}   50.65{col 49}{space 3}0.000{col 57}{space 4} 4.513448{col 70}{space 3} 4.876839
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4553401
        {txt}sigma_e {c |} {res} 1.2370778
            {txt}rho {c |} {res} .58053627{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist   $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,410
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,555

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0300{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1068{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0929{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}16{txt},{res}4554{txt}){col 67}={col 70}{res}    13.06
{txt}corr(u_i, Xb){col 16}= {res}0.1195{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2} .0590865{col 29}{space 2} .0159855{col 40}{space 1}    3.70{col 49}{space 3}0.000{col 57}{space 4} .0277472{col 70}{space 3} .0904258
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}-.0005131{col 29}{space 2} .0066863{col 40}{space 1}   -0.08{col 49}{space 3}0.939{col 57}{space 4}-.0136215{col 70}{space 3} .0125952
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0595515{col 29}{space 2} .0132052{col 40}{space 1}    4.51{col 49}{space 3}0.000{col 57}{space 4} .0336629{col 70}{space 3} .0854401
{txt}dependent_share {c |}{col 17}{res}{space 2}-.1583395{col 29}{space 2} .0960185{col 40}{space 1}   -1.65{col 49}{space 3}0.099{col 57}{space 4}-.3465823{col 70}{space 3} .0299033
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0096401{col 29}{space 2}  .002929{col 40}{space 1}    3.29{col 49}{space 3}0.001{col 57}{space 4} .0038979{col 70}{space 3} .0153823
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0154357{col 29}{space 2} .0858614{col 40}{space 1}   -0.18{col 49}{space 3}0.857{col 57}{space 4}-.1837656{col 70}{space 3} .1528943
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}  .214903{col 29}{space 2} .0481536{col 40}{space 1}    4.46{col 49}{space 3}0.000{col 57}{space 4} .1204986{col 70}{space 3} .3093074
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1954251{col 29}{space 2} .1550152{col 40}{space 1}   -1.26{col 49}{space 3}0.207{col 57}{space 4}  -.49933{col 70}{space 3} .1084798
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .173648{col 29}{space 2} .0377589{col 40}{space 1}    4.60{col 49}{space 3}0.000{col 57}{space 4} .0996222{col 70}{space 3} .2476738
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .122499{col 29}{space 2} .0463119{col 40}{space 1}    2.65{col 49}{space 3}0.008{col 57}{space 4} .0317051{col 70}{space 3} .2132929
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0835163{col 29}{space 2} .0631139{col 40}{space 1}    1.32{col 49}{space 3}0.186{col 57}{space 4}-.0402177{col 70}{space 3} .2072502
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}  .231584{col 29}{space 2} .0499306{col 40}{space 1}    4.64{col 49}{space 3}0.000{col 57}{space 4} .1336959{col 70}{space 3} .3294722
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} -.006984{col 29}{space 2} .0361322{col 40}{space 1}   -0.19{col 49}{space 3}0.847{col 57}{space 4}-.0778206{col 70}{space 3} .0638526
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .011011{col 29}{space 2} .0044569{col 40}{space 1}    2.47{col 49}{space 3}0.014{col 57}{space 4} .0022732{col 70}{space 3} .0197487
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0389494{col 29}{space 2} .0466116{col 40}{space 1}    0.84{col 49}{space 3}0.403{col 57}{space 4}-.0524318{col 70}{space 3} .1303307
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.1622233{col 29}{space 2} .0231372{col 40}{space 1}   -7.01{col 49}{space 3}0.000{col 57}{space 4}-.2075835{col 70}{space 3}-.1168631
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.970735{col 29}{space 2} .2024709{col 40}{space 1}   14.67{col 49}{space 3}0.000{col 57}{space 4} 2.573794{col 70}{space 3} 3.367677
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2230322
        {txt}sigma_e {c |} {res} 1.0776877
            {txt}rho {c |} {res} .56292236{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_town sum_town  $xlist   $year_MALAWI  if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     4,626
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     1,571

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0259{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2417{col 63}{txt}avg{col 67}={col 69}{res}       2.9
{txt}     overall = {res}0.1516{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}1570{txt}){col 67}={col 70}{res}     4.37
{txt}corr(u_i, Xb){col 16}= {res}0.2703{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2}  .025624{col 29}{space 2} .0267814{col 40}{space 1}    0.96{col 49}{space 3}0.339{col 57}{space 4}-.0269071{col 70}{space 3}  .078155
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}  .003218{col 29}{space 2} .0138789{col 40}{space 1}    0.23{col 49}{space 3}0.817{col 57}{space 4}-.0240051{col 70}{space 3} .0304411
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0486976{col 29}{space 2} .0184507{col 40}{space 1}    2.64{col 49}{space 3}0.008{col 57}{space 4} .0125069{col 70}{space 3} .0848882
{txt}dependent_share {c |}{col 17}{res}{space 2}-.2433188{col 29}{space 2}  .149148{col 40}{space 1}   -1.63{col 49}{space 3}0.103{col 57}{space 4}-.5358691{col 70}{space 3} .0492316
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} -.001635{col 29}{space 2} .0040547{col 40}{space 1}   -0.40{col 49}{space 3}0.687{col 57}{space 4}-.0095882{col 70}{space 3} .0063183
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.1559251{col 29}{space 2} .0937796{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4}-.3398716{col 70}{space 3} .0280214
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1983293{col 29}{space 2} .0786248{col 40}{space 1}    2.52{col 49}{space 3}0.012{col 57}{space 4} .0441087{col 70}{space 3} .3525499
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2388254{col 29}{space 2} .1909849{col 40}{space 1}    1.25{col 49}{space 3}0.211{col 57}{space 4}-.1357869{col 70}{space 3} .6134376
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .086331{col 29}{space 2}  .070079{col 40}{space 1}    1.23{col 49}{space 3}0.218{col 57}{space 4}-.0511272{col 70}{space 3} .2237893
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1742317{col 29}{space 2} .1395315{col 40}{space 1}    1.25{col 49}{space 3}0.212{col 57}{space 4}-.0994561{col 70}{space 3} .4479194
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1122965{col 29}{space 2} .0816503{col 40}{space 1}    1.38{col 49}{space 3}0.169{col 57}{space 4}-.0478586{col 70}{space 3} .2724516
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2420119{col 29}{space 2} .0565381{col 40}{space 1}    4.28{col 49}{space 3}0.000{col 57}{space 4} .1311138{col 70}{space 3}   .35291
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1258991{col 29}{space 2} .0494591{col 40}{space 1}   -2.55{col 49}{space 3}0.011{col 57}{space 4}-.2229119{col 70}{space 3}-.0288864
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0630315{col 29}{space 2} .0478453{col 40}{space 1}    1.32{col 49}{space 3}0.188{col 57}{space 4} -.030816{col 70}{space 3}  .156879
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1417402{col 29}{space 2} .0762385{col 40}{space 1}    1.86{col 49}{space 3}0.063{col 57}{space 4}-.0077997{col 70}{space 3} .2912802
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .1424342{col 29}{space 2} .0847266{col 40}{space 1}    1.68{col 49}{space 3}0.093{col 57}{space 4} -.023755{col 70}{space 3} .3086234
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .0861317{col 29}{space 2} .0530636{col 40}{space 1}    1.62{col 49}{space 3}0.105{col 57}{space 4}-.0179512{col 70}{space 3} .1902147
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.350914{col 29}{space 2} .3429569{col 40}{space 1}   15.60{col 49}{space 3}0.000{col 57}{space 4} 4.678212{col 70}{space 3} 6.023615
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3483609
        {txt}sigma_e {c |} {res} 1.2904676
            {txt}rho {c |} {res} .52192847{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_town sum_town  $xlist    $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     6,536
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,837

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0496{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0091{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0089{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}16{txt},{res}3836{txt}){col 67}={col 70}{res}     8.22
{txt}corr(u_i, Xb){col 16}= {res}-0.7210{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2} .1035333{col 29}{space 2} .0306519{col 40}{space 1}    3.38{col 49}{space 3}0.001{col 57}{space 4} .0434377{col 70}{space 3} .1636289
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}-.0206359{col 29}{space 2}  .002946{col 40}{space 1}   -7.00{col 49}{space 3}0.000{col 57}{space 4}-.0264118{col 70}{space 3}  -.01486
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0374874{col 29}{space 2} .0186276{col 40}{space 1}   -2.01{col 49}{space 3}0.044{col 57}{space 4}-.0740083{col 70}{space 3}-.0009665
{txt}dependent_share {c |}{col 17}{res}{space 2} .2611481{col 29}{space 2} .2377952{col 40}{space 1}    1.10{col 49}{space 3}0.272{col 57}{space 4}-.2050689{col 70}{space 3} .7273652
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0078051{col 29}{space 2} .0056024{col 40}{space 1}    1.39{col 49}{space 3}0.164{col 57}{space 4}-.0031788{col 70}{space 3} .0187891
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .2237886{col 29}{space 2} .1519777{col 40}{space 1}    1.47{col 49}{space 3}0.141{col 57}{space 4}-.0741762{col 70}{space 3} .5217534
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1941921{col 29}{space 2} .0870393{col 40}{space 1}    2.23{col 49}{space 3}0.026{col 57}{space 4} .0235443{col 70}{space 3}   .36484
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .3196812{col 29}{space 2} .1089899{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .1059974{col 70}{space 3} .5333649
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1358326{col 29}{space 2} .0777605{col 40}{space 1}    1.75{col 49}{space 3}0.081{col 57}{space 4}-.0166233{col 70}{space 3} .2882886
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .2043745{col 29}{space 2} .1240761{col 40}{space 1}    1.65{col 49}{space 3}0.100{col 57}{space 4} -.038887{col 70}{space 3}  .447636
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1696587{col 29}{space 2} .0886862{col 40}{space 1}    1.91{col 49}{space 3}0.056{col 57}{space 4}-.0042179{col 70}{space 3} .3435354
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}-.1364162{col 29}{space 2} .0694315{col 40}{space 1}   -1.96{col 49}{space 3}0.050{col 57}{space 4}-.2725423{col 70}{space 3}  -.00029
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0218792{col 29}{space 2}  .066853{col 40}{space 1}    0.33{col 49}{space 3}0.743{col 57}{space 4}-.1091917{col 70}{space 3}   .15295
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0068521{col 29}{space 2} .0026145{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} .0017263{col 70}{space 3}  .011978
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1607369{col 29}{space 2} .3283631{col 40}{space 1}    0.49{col 49}{space 3}0.625{col 57}{space 4}-.4830461{col 70}{space 3} .8045199
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2} .4964984{col 29}{space 2} .0554222{col 40}{space 1}    8.96{col 49}{space 3}0.000{col 57}{space 4} .3878387{col 70}{space 3} .6051582
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.617248{col 29}{space 2} .3730963{col 40}{space 1}   15.06{col 49}{space 3}0.000{col 57}{space 4} 4.885762{col 70}{space 3} 6.348734
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 2.0013647
        {txt}sigma_e {c |} {res} 1.3965162
            {txt}rho {c |} {res} .67254035{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist   $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    15,063
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     7,154

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0426{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1390{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.1139{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}18{txt},{res}7153{txt}){col 67}={col 70}{res}    17.67
{txt}corr(u_i, Xb){col 16}= {res}0.1538{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2} .0619796{col 29}{space 2} .0156318{col 40}{space 1}    3.96{col 49}{space 3}0.000{col 57}{space 4} .0313366{col 70}{space 3} .0926226
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}-.0085792{col 29}{space 2} .0058164{col 40}{space 1}   -1.47{col 49}{space 3}0.140{col 57}{space 4} -.019981{col 70}{space 3} .0028227
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0278438{col 29}{space 2} .0098786{col 40}{space 1}    2.82{col 49}{space 3}0.005{col 57}{space 4} .0084789{col 70}{space 3} .0472088
{txt}dependent_share {c |}{col 17}{res}{space 2} .1712763{col 29}{space 2} .0886069{col 40}{space 1}    1.93{col 49}{space 3}0.053{col 57}{space 4}-.0024195{col 70}{space 3} .3449721
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0027164{col 29}{space 2} .0023052{col 40}{space 1}   -1.18{col 49}{space 3}0.239{col 57}{space 4}-.0072353{col 70}{space 3} .0018026
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0110832{col 29}{space 2} .0822561{col 40}{space 1}   -0.13{col 49}{space 3}0.893{col 57}{space 4}-.1723295{col 70}{space 3} .1501631
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0362514{col 29}{space 2} .0395514{col 40}{space 1}    0.92{col 49}{space 3}0.359{col 57}{space 4}-.0412811{col 70}{space 3} .1137839
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .0008348{col 29}{space 2} .0416836{col 40}{space 1}    0.02{col 49}{space 3}0.984{col 57}{space 4}-.0808774{col 70}{space 3}  .082547
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1502401{col 29}{space 2} .0404754{col 40}{space 1}    3.71{col 49}{space 3}0.000{col 57}{space 4} .0708964{col 70}{space 3} .2295837
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0819763{col 29}{space 2} .0492117{col 40}{space 1}    1.67{col 49}{space 3}0.096{col 57}{space 4}-.0144931{col 70}{space 3} .1784457
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2285951{col 29}{space 2} .0568003{col 40}{space 1}    4.02{col 49}{space 3}0.000{col 57}{space 4} .1172496{col 70}{space 3} .3399405
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2816354{col 29}{space 2}  .043179{col 40}{space 1}    6.52{col 49}{space 3}0.000{col 57}{space 4} .1969919{col 70}{space 3} .3662789
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0522106{col 29}{space 2} .0600663{col 40}{space 1}    0.87{col 49}{space 3}0.385{col 57}{space 4}-.0655372{col 70}{space 3} .1699583
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0080926{col 29}{space 2} .0113688{col 40}{space 1}    0.71{col 49}{space 3}0.477{col 57}{space 4}-.0141937{col 70}{space 3} .0303789
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .2297594{col 29}{space 2} .1024619{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} .0289037{col 70}{space 3} .4306151
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.5848326{col 29}{space 2} .0555634{col 40}{space 1}  -10.53{col 49}{space 3}0.000{col 57}{space 4}-.6937533{col 70}{space 3}-.4759119
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2} -.510124{col 29}{space 2} .0546881{col 40}{space 1}   -9.33{col 49}{space 3}0.000{col 57}{space 4}-.6173287{col 70}{space 3}-.4029192
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.3278177{col 29}{space 2} .0540711{col 40}{space 1}   -6.06{col 49}{space 3}0.000{col 57}{space 4} -.433813{col 70}{space 3}-.2218224
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.486876{col 29}{space 2} .1836386{col 40}{space 1}   29.88{col 49}{space 3}0.000{col 57}{space 4}  5.12689{col 70}{space 3} 5.846862
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4739282
        {txt}sigma_e {c |} {res} 1.2232495
            {txt}rho {c |} {res} .59214514{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist   $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,830
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,710

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0288{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1046{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.0808{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}18{txt},{res}5709{txt}){col 67}={col 70}{res}     9.58
{txt}corr(u_i, Xb){col 16}= {res}0.0698{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2}-.0089983{col 29}{space 2} .0210467{col 40}{space 1}   -0.43{col 49}{space 3}0.669{col 57}{space 4}-.0502579{col 70}{space 3} .0322613
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2}-.0029135{col 29}{space 2} .0094362{col 40}{space 1}   -0.31{col 49}{space 3}0.758{col 57}{space 4}-.0214121{col 70}{space 3} .0155852
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0296316{col 29}{space 2}  .011028{col 40}{space 1}    2.69{col 49}{space 3}0.007{col 57}{space 4} .0080125{col 70}{space 3} .0512507
{txt}dependent_share {c |}{col 17}{res}{space 2} .3819467{col 29}{space 2} .1092294{col 40}{space 1}    3.50{col 49}{space 3}0.000{col 57}{space 4} .1678157{col 70}{space 3} .5960777
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0096744{col 29}{space 2} .0035824{col 40}{space 1}   -2.70{col 49}{space 3}0.007{col 57}{space 4}-.0166972{col 70}{space 3}-.0026515
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0143974{col 29}{space 2} .1046225{col 40}{space 1}    0.14{col 49}{space 3}0.891{col 57}{space 4}-.1907023{col 70}{space 3} .2194972
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0083075{col 29}{space 2} .0645893{col 40}{space 1}    0.13{col 49}{space 3}0.898{col 57}{space 4} -.118312{col 70}{space 3}  .134927
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2536207{col 29}{space 2} .0866181{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .0838164{col 70}{space 3} .4234251
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2674459{col 29}{space 2} .0488687{col 40}{space 1}    5.47{col 49}{space 3}0.000{col 57}{space 4} .1716448{col 70}{space 3}  .363247
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1010178{col 29}{space 2} .0572962{col 40}{space 1}    1.76{col 49}{space 3}0.078{col 57}{space 4}-.0113045{col 70}{space 3}   .21334
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1038536{col 29}{space 2} .0388401{col 40}{space 1}    2.67{col 49}{space 3}0.008{col 57}{space 4} .0277123{col 70}{space 3} .1799948
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2169615{col 29}{space 2} .0403992{col 40}{space 1}    5.37{col 49}{space 3}0.000{col 57}{space 4} .1377638{col 70}{space 3} .2961592
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0285413{col 29}{space 2} .0446824{col 40}{space 1}   -0.64{col 49}{space 3}0.523{col 57}{space 4}-.1161358{col 70}{space 3} .0590532
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0159907{col 29}{space 2} .0069901{col 40}{space 1}    2.29{col 49}{space 3}0.022{col 57}{space 4} .0022875{col 70}{space 3} .0296938
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0151613{col 29}{space 2} .0497879{col 40}{space 1}    0.30{col 49}{space 3}0.761{col 57}{space 4}-.0824418{col 70}{space 3} .1127644
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.1480808{col 29}{space 2}   .04187{col 40}{space 1}   -3.54{col 49}{space 3}0.000{col 57}{space 4} -.230162{col 70}{space 3}-.0659997
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.1279835{col 29}{space 2} .0370868{col 40}{space 1}   -3.45{col 49}{space 3}0.001{col 57}{space 4}-.2006878{col 70}{space 3}-.0552793
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2}  .141051{col 29}{space 2} .0438984{col 40}{space 1}    3.21{col 49}{space 3}0.001{col 57}{space 4} .0549935{col 70}{space 3} .2271084
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.541255{col 29}{space 2} .2466453{col 40}{space 1}   22.47{col 49}{space 3}0.000{col 57}{space 4} 5.057737{col 70}{space 3} 6.024774
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.315923
        {txt}sigma_e {c |} {res} 1.2283347
            {txt}rho {c |} {res} .53438513{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_town sum_town  $xlist   $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    16,114
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,402

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0443{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2189{col 63}{txt}avg{col 67}={col 69}{res}       3.7
{txt}     overall = {res}0.1443{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}20{txt},{res}4401{txt}){col 67}={col 70}{res}    25.07
{txt}corr(u_i, Xb){col 16}= {res}0.2151{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_town {c |}{col 17}{res}{space 2} .0056444{col 29}{space 2} .0141168{col 40}{space 1}    0.40{col 49}{space 3}0.689{col 57}{space 4}-.0220316{col 70}{space 3} .0333203
{txt}{space 7}sum_town {c |}{col 17}{res}{space 2} -.007118{col 29}{space 2} .0051889{col 40}{space 1}   -1.37{col 49}{space 3}0.170{col 57}{space 4}-.0172909{col 70}{space 3} .0030549
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0212549{col 29}{space 2} .0089937{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0036228{col 70}{space 3}  .038887
{txt}dependent_share {c |}{col 17}{res}{space 2} .1086739{col 29}{space 2} .0823427{col 40}{space 1}    1.32{col 49}{space 3}0.187{col 57}{space 4}-.0527592{col 70}{space 3} .2701071
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0066744{col 29}{space 2} .0028331{col 40}{space 1}    2.36{col 49}{space 3}0.019{col 57}{space 4} .0011201{col 70}{space 3} .0122287
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0616244{col 29}{space 2} .0673269{col 40}{space 1}    0.92{col 49}{space 3}0.360{col 57}{space 4}-.0703701{col 70}{space 3}  .193619
{txt}{space 6}head_read {c |}{col 17}{res}{space 2}  .200829{col 29}{space 2} .0476544{col 40}{space 1}    4.21{col 49}{space 3}0.000{col 57}{space 4} .1074023{col 70}{space 3} .2942557
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2445842{col 29}{space 2} .0564343{col 40}{space 1}    4.33{col 49}{space 3}0.000{col 57}{space 4} .1339446{col 70}{space 3} .3552237
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2546164{col 29}{space 2} .0378262{col 40}{space 1}    6.73{col 49}{space 3}0.000{col 57}{space 4}  .180458{col 70}{space 3} .3287747
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .3281478{col 29}{space 2} .0387967{col 40}{space 1}    8.46{col 49}{space 3}0.000{col 57}{space 4} .2520868{col 70}{space 3} .4042087
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0459141{col 29}{space 2} .0308384{col 40}{space 1}    1.49{col 49}{space 3}0.137{col 57}{space 4}-.0145447{col 70}{space 3} .1063729
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2109735{col 29}{space 2}  .032234{col 40}{space 1}    6.55{col 49}{space 3}0.000{col 57}{space 4} .1477786{col 70}{space 3} .2741684
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0452162{col 29}{space 2} .0279727{col 40}{space 1}    1.62{col 49}{space 3}0.106{col 57}{space 4}-.0096243{col 70}{space 3} .1000566
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0005768{col 29}{space 2} .0015518{col 40}{space 1}    0.37{col 49}{space 3}0.710{col 57}{space 4}-.0024654{col 70}{space 3}  .003619
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2}  .060297{col 29}{space 2} .0369622{col 40}{space 1}    1.63{col 49}{space 3}0.103{col 57}{space 4}-.0121675{col 70}{space 3} .1327616
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1184251{col 29}{space 2} .0405026{col 40}{space 1}   -2.92{col 49}{space 3}0.003{col 57}{space 4}-.1978305{col 70}{space 3}-.0390197
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0084856{col 29}{space 2} .0368641{col 40}{space 1}   -0.23{col 49}{space 3}0.818{col 57}{space 4}-.0807577{col 70}{space 3} .0637865
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}  .356856{col 29}{space 2} .0364108{col 40}{space 1}    9.80{col 49}{space 3}0.000{col 57}{space 4} .2854725{col 70}{space 3} .4282395
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0950521{col 29}{space 2} .0358278{col 40}{space 1}    2.65{col 49}{space 3}0.008{col 57}{space 4} .0248117{col 70}{space 3} .1652925
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2}  .269741{col 29}{space 2} .0332235{col 40}{space 1}    8.12{col 49}{space 3}0.000{col 57}{space 4} .2046063{col 70}{space 3} .3348757
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.468509{col 29}{space 2} .1833368{col 40}{space 1}   24.37{col 49}{space 3}0.000{col 57}{space 4} 4.109077{col 70}{space 3} 4.827942
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2184547
        {txt}sigma_e {c |} {res} 1.2678475
            {txt}rho {c |} {res} .48014188{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S26_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S26_fe.rtf not found)
(output written to {browse  `"S26_fe.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                                  S27                                         *
. ********************************************************************************
. eststo clear
{txt}
{com}. xtreg hdd9  pdd9_dist  sum_dist  $xlist   i.year   , cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    65,579
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}    27,229

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0283{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1478{col 63}{txt}avg{col 67}={col 69}{res}       2.4
{txt}     overall = {res}0.1088{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}25{txt},{res}27228{txt}){col 67}={col 70}{res}    40.70
{txt}corr(u_i, Xb){col 16}= {res}0.1854{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2} .0301194{col 29}{space 2}  .009078{col 40}{space 1}    3.32{col 49}{space 3}0.001{col 57}{space 4}  .012326{col 70}{space 3} .0479128
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2}-.0010908{col 29}{space 2} .0005568{col 40}{space 1}   -1.96{col 49}{space 3}0.050{col 57}{space 4}-.0021822{col 70}{space 3} 6.12e-07
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0301561{col 29}{space 2} .0049547{col 40}{space 1}    6.09{col 49}{space 3}0.000{col 57}{space 4} .0204446{col 70}{space 3} .0398676
{txt}dependent_share {c |}{col 17}{res}{space 2}  .111607{col 29}{space 2} .0440164{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .0253327{col 70}{space 3} .1978814
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0022233{col 29}{space 2} .0013483{col 40}{space 1}   -1.65{col 49}{space 3}0.099{col 57}{space 4} -.004866{col 70}{space 3} .0004194
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0560182{col 29}{space 2} .0372872{col 40}{space 1}   -1.50{col 49}{space 3}0.133{col 57}{space 4}-.1291029{col 70}{space 3} .0170666
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1216182{col 29}{space 2} .0225445{col 40}{space 1}    5.39{col 49}{space 3}0.000{col 57}{space 4} .0774299{col 70}{space 3} .1658066
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .1160556{col 29}{space 2} .0293602{col 40}{space 1}    3.95{col 49}{space 3}0.000{col 57}{space 4}  .058508{col 70}{space 3} .1736031
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1553908{col 29}{space 2}  .019455{col 40}{space 1}    7.99{col 49}{space 3}0.000{col 57}{space 4} .1172581{col 70}{space 3} .1935236
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1332894{col 29}{space 2} .0230132{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 57}{space 4} .0881823{col 70}{space 3} .1783964
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1223372{col 29}{space 2} .0199309{col 40}{space 1}    6.14{col 49}{space 3}0.000{col 57}{space 4} .0832716{col 70}{space 3} .1614028
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2126878{col 29}{space 2} .0183003{col 40}{space 1}   11.62{col 49}{space 3}0.000{col 57}{space 4} .1768184{col 70}{space 3} .2485572
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0539912{col 29}{space 2} .0173338{col 40}{space 1}    3.11{col 49}{space 3}0.002{col 57}{space 4}  .020016{col 70}{space 3} .0879664
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0050066{col 29}{space 2}  .001771{col 40}{space 1}    2.83{col 49}{space 3}0.005{col 57}{space 4} .0015353{col 70}{space 3} .0084779
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0662868{col 29}{space 2} .0232937{col 40}{space 1}    2.85{col 49}{space 3}0.004{col 57}{space 4} .0206298{col 70}{space 3} .1119437
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}2009  {c |}{col 17}{res}{space 2}-.1594176{col 29}{space 2} .0497809{col 40}{space 1}   -3.20{col 49}{space 3}0.001{col 57}{space 4}-.2569907{col 70}{space 3}-.0618445
{txt}{space 10}2010  {c |}{col 17}{res}{space 2} .1007462{col 29}{space 2} .0369908{col 40}{space 1}    2.72{col 49}{space 3}0.006{col 57}{space 4} .0282423{col 70}{space 3} .1732502
{txt}{space 10}2011  {c |}{col 17}{res}{space 2} .2236507{col 29}{space 2} .0430056{col 40}{space 1}    5.20{col 49}{space 3}0.000{col 57}{space 4} .1393575{col 70}{space 3}  .307944
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .0975609{col 29}{space 2} .0381248{col 40}{space 1}    2.56{col 49}{space 3}0.011{col 57}{space 4} .0228343{col 70}{space 3} .1722874
{txt}{space 10}2013  {c |}{col 17}{res}{space 2} .2758934{col 29}{space 2} .0432856{col 40}{space 1}    6.37{col 49}{space 3}0.000{col 57}{space 4} .1910514{col 70}{space 3} .3607354
{txt}{space 10}2014  {c |}{col 17}{res}{space 2} .1695226{col 29}{space 2}  .048583{col 40}{space 1}    3.49{col 49}{space 3}0.000{col 57}{space 4} .0742975{col 70}{space 3} .2647477
{txt}{space 10}2015  {c |}{col 17}{res}{space 2}  .337313{col 29}{space 2} .0418314{col 40}{space 1}    8.06{col 49}{space 3}0.000{col 57}{space 4} .2553214{col 70}{space 3} .4193045
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-.0425727{col 29}{space 2} .0622739{col 40}{space 1}   -0.68{col 49}{space 3}0.494{col 57}{space 4}-.1646326{col 70}{space 3} .0794872
{txt}{space 10}2018  {c |}{col 17}{res}{space 2}  .551076{col 29}{space 2}  .048123{col 40}{space 1}   11.45{col 49}{space 3}0.000{col 57}{space 4} .4567525{col 70}{space 3} .6453994
{txt}{space 10}2019  {c |}{col 17}{res}{space 2} .2707985{col 29}{space 2} .0471098{col 40}{space 1}    5.75{col 49}{space 3}0.000{col 57}{space 4} .1784608{col 70}{space 3} .3631362
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 4.603638{col 29}{space 2} .1011192{col 40}{space 1}   45.53{col 49}{space 3}0.000{col 57}{space 4} 4.405439{col 70}{space 3} 4.801836
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4513319
        {txt}sigma_e {c |} {res}  1.237148
            {txt}rho {c |} {res} .57916482{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est1
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist  $year_ETHIOPIA if country==3, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,410
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,555

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0303{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0746{col 63}{txt}avg{col 67}={col 69}{res}       2.5
{txt}     overall = {res}0.0717{col 63}{txt}max{col 67}={col 69}{res}         3

{txt}{col 49}F({res}16{txt},{res}4554{txt}){col 67}={col 70}{res}    13.14
{txt}corr(u_i, Xb){col 16}= {res}0.0430{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2} .0616344{col 29}{space 2} .0164646{col 40}{space 1}    3.74{col 49}{space 3}0.000{col 57}{space 4} .0293559{col 70}{space 3}  .093913
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2} .0045099{col 29}{space 2} .0059076{col 40}{space 1}    0.76{col 49}{space 3}0.445{col 57}{space 4}-.0070719{col 70}{space 3} .0160917
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0592096{col 29}{space 2} .0132097{col 40}{space 1}    4.48{col 49}{space 3}0.000{col 57}{space 4} .0333123{col 70}{space 3}  .085107
{txt}dependent_share {c |}{col 17}{res}{space 2}-.1575828{col 29}{space 2} .0959531{col 40}{space 1}   -1.64{col 49}{space 3}0.101{col 57}{space 4}-.3456974{col 70}{space 3} .0305317
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0093306{col 29}{space 2} .0029351{col 40}{space 1}    3.18{col 49}{space 3}0.001{col 57}{space 4} .0035763{col 70}{space 3} .0150848
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0151222{col 29}{space 2} .0857804{col 40}{space 1}   -0.18{col 49}{space 3}0.860{col 57}{space 4}-.1832934{col 70}{space 3} .1530489
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2153536{col 29}{space 2} .0481138{col 40}{space 1}    4.48{col 49}{space 3}0.000{col 57}{space 4} .1210272{col 70}{space 3}   .30968
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.1951712{col 29}{space 2}  .155176{col 40}{space 1}   -1.26{col 49}{space 3}0.209{col 57}{space 4}-.4993914{col 70}{space 3} .1090489
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1725895{col 29}{space 2} .0377403{col 40}{space 1}    4.57{col 49}{space 3}0.000{col 57}{space 4} .0986003{col 70}{space 3} .2465787
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1187046{col 29}{space 2} .0462329{col 40}{space 1}    2.57{col 49}{space 3}0.010{col 57}{space 4} .0280656{col 70}{space 3} .2093435
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0824429{col 29}{space 2} .0631269{col 40}{space 1}    1.31{col 49}{space 3}0.192{col 57}{space 4}-.0413165{col 70}{space 3} .2062023
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2316855{col 29}{space 2} .0499123{col 40}{space 1}    4.64{col 49}{space 3}0.000{col 57}{space 4} .1338332{col 70}{space 3} .3295378
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0101845{col 29}{space 2} .0361209{col 40}{space 1}   -0.28{col 49}{space 3}0.778{col 57}{space 4}-.0809989{col 70}{space 3} .0606299
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0110184{col 29}{space 2}  .004456{col 40}{space 1}    2.47{col 49}{space 3}0.013{col 57}{space 4} .0022825{col 70}{space 3} .0197542
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0369898{col 29}{space 2} .0466474{col 40}{space 1}    0.79{col 49}{space 3}0.428{col 57}{space 4}-.0544617{col 70}{space 3} .1284413
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}-.1683501{col 29}{space 2} .0233166{col 40}{space 1}   -7.22{col 49}{space 3}0.000{col 57}{space 4}-.2140619{col 70}{space 3}-.1226384
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.869298{col 29}{space 2}  .197989{col 40}{space 1}   14.49{col 49}{space 3}0.000{col 57}{space 4} 2.481143{col 70}{space 3} 3.257452
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res}  1.237338
        {txt}sigma_e {c |} {res} 1.0775436
            {txt}rho {c |} {res} .56870181{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est2
{txt}
{com}. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist  $year_MALAWI  if country==6, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     4,626
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     1,571

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0260{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2903{col 63}{txt}avg{col 67}={col 69}{res}       2.9
{txt}     overall = {res}0.1837{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}17{txt},{res}1570{txt}){col 67}={col 70}{res}     4.45
{txt}corr(u_i, Xb){col 16}= {res}0.3163{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2}-.0458541{col 29}{space 2} .0415057{col 40}{space 1}   -1.10{col 49}{space 3}0.269{col 57}{space 4}-.1272666{col 70}{space 3} .0355584
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2} -.000425{col 29}{space 2} .0032275{col 40}{space 1}   -0.13{col 49}{space 3}0.895{col 57}{space 4}-.0067557{col 70}{space 3} .0059057
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0474816{col 29}{space 2} .0184145{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0113621{col 70}{space 3} .0836011
{txt}dependent_share {c |}{col 17}{res}{space 2}-.2442262{col 29}{space 2} .1493896{col 40}{space 1}   -1.63{col 49}{space 3}0.102{col 57}{space 4}-.5372504{col 70}{space 3}  .048798
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0014453{col 29}{space 2} .0040417{col 40}{space 1}   -0.36{col 49}{space 3}0.721{col 57}{space 4} -.009373{col 70}{space 3} .0064825
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} -.156147{col 29}{space 2} .0937237{col 40}{space 1}   -1.67{col 49}{space 3}0.096{col 57}{space 4}-.3399838{col 70}{space 3} .0276898
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2024347{col 29}{space 2} .0788177{col 40}{space 1}    2.57{col 49}{space 3}0.010{col 57}{space 4} .0478357{col 70}{space 3} .3570337
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2425615{col 29}{space 2} .1899342{col 40}{space 1}    1.28{col 49}{space 3}0.202{col 57}{space 4}-.1299899{col 70}{space 3} .6151129
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .0895135{col 29}{space 2} .0700854{col 40}{space 1}    1.28{col 49}{space 3}0.202{col 57}{space 4}-.0479574{col 70}{space 3} .2269843
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .193332{col 29}{space 2} .1387243{col 40}{space 1}    1.39{col 49}{space 3}0.164{col 57}{space 4}-.0787725{col 70}{space 3} .4654364
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1151536{col 29}{space 2} .0814328{col 40}{space 1}    1.41{col 49}{space 3}0.158{col 57}{space 4}-.0445749{col 70}{space 3} .2748821
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}  .244829{col 29}{space 2} .0564599{col 40}{space 1}    4.34{col 49}{space 3}0.000{col 57}{space 4} .1340841{col 70}{space 3} .3555738
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.1204562{col 29}{space 2} .0495544{col 40}{space 1}   -2.43{col 49}{space 3}0.015{col 57}{space 4} -.217656{col 70}{space 3}-.0232563
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2}  .064734{col 29}{space 2} .0476546{col 40}{space 1}    1.36{col 49}{space 3}0.175{col 57}{space 4}-.0287393{col 70}{space 3} .1582074
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1404591{col 29}{space 2}  .076201{col 40}{space 1}    1.84{col 49}{space 3}0.065{col 57}{space 4}-.0090075{col 70}{space 3} .2899256
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2} .1367884{col 29}{space 2}  .079005{col 40}{space 1}    1.73{col 49}{space 3}0.084{col 57}{space 4}-.0181781{col 70}{space 3} .2917548
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2}  .089302{col 29}{space 2} .0527236{col 40}{space 1}    1.69{col 49}{space 3}0.091{col 57}{space 4}-.0141141{col 70}{space 3} .1927182
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.890767{col 29}{space 2} .4048541{col 40}{space 1}   14.55{col 49}{space 3}0.000{col 57}{space 4} 5.096655{col 70}{space 3} 6.684878
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3250231
        {txt}sigma_e {c |} {res} 1.2904179
            {txt}rho {c |} {res} .51322881{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est3
{txt}
{com}. 
. xtreg hdd9 pdd9_dist  sum_dist  $xlist  $year_NIGER if country==1, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}     6,536
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     3,837

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0443{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0039{col 63}{txt}avg{col 67}={col 69}{res}       1.7
{txt}     overall = {res}0.0004{col 63}{txt}max{col 67}={col 69}{res}         2

{txt}{col 49}F({res}16{txt},{res}3836{txt}){col 67}={col 70}{res}     6.94
{txt}corr(u_i, Xb){col 16}= {res}-0.5581{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2} .0593814{col 29}{space 2} .0453482{col 40}{space 1}    1.31{col 49}{space 3}0.190{col 57}{space 4}-.0295276{col 70}{space 3} .1482904
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2}-.0105497{col 29}{space 2} .0017293{col 40}{space 1}   -6.10{col 49}{space 3}0.000{col 57}{space 4}-.0139402{col 70}{space 3}-.0071591
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2}-.0368447{col 29}{space 2} .0185006{col 40}{space 1}   -1.99{col 49}{space 3}0.046{col 57}{space 4}-.0731166{col 70}{space 3}-.0005728
{txt}dependent_share {c |}{col 17}{res}{space 2} .2568869{col 29}{space 2} .2371757{col 40}{space 1}    1.08{col 49}{space 3}0.279{col 57}{space 4}-.2081156{col 70}{space 3} .7218894
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0090495{col 29}{space 2} .0055793{col 40}{space 1}    1.62{col 49}{space 3}0.105{col 57}{space 4}-.0018892{col 70}{space 3} .0199882
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .2412514{col 29}{space 2} .1527501{col 40}{space 1}    1.58{col 49}{space 3}0.114{col 57}{space 4}-.0582277{col 70}{space 3} .5407305
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .2053985{col 29}{space 2} .0870761{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0346786{col 70}{space 3} .3761184
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .3386788{col 29}{space 2} .1100098{col 40}{space 1}    3.08{col 49}{space 3}0.002{col 57}{space 4} .1229955{col 70}{space 3}  .554362
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .1505853{col 29}{space 2} .0781167{col 40}{space 1}    1.93{col 49}{space 3}0.054{col 57}{space 4} -.002569{col 70}{space 3} .3037396
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .1562049{col 29}{space 2} .1252353{col 40}{space 1}    1.25{col 49}{space 3}0.212{col 57}{space 4}-.0893293{col 70}{space 3} .4017391
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2}  .166511{col 29}{space 2} .0888181{col 40}{space 1}    1.87{col 49}{space 3}0.061{col 57}{space 4}-.0076242{col 70}{space 3} .3406462
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} -.123189{col 29}{space 2} .0694729{col 40}{space 1}   -1.77{col 49}{space 3}0.076{col 57}{space 4}-.2593963{col 70}{space 3} .0130183
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0293401{col 29}{space 2} .0672906{col 40}{space 1}    0.44{col 49}{space 3}0.663{col 57}{space 4}-.1025887{col 70}{space 3} .1612688
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0050453{col 29}{space 2} .0026151{col 40}{space 1}    1.93{col 49}{space 3}0.054{col 57}{space 4}-.0000818{col 70}{space 3} .0101724
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .1932424{col 29}{space 2} .3302749{col 40}{space 1}    0.59{col 49}{space 3}0.559{col 57}{space 4}-.4542888{col 70}{space 3} .8407735
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}  .532223{col 29}{space 2} .0598124{col 40}{space 1}    8.90{col 49}{space 3}0.000{col 57}{space 4} .4149559{col 70}{space 3} .6494901
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.768615{col 29}{space 2} .4599952{col 40}{space 1}   12.54{col 49}{space 3}0.000{col 57}{space 4} 4.866756{col 70}{space 3} 6.670474
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.7183239
        {txt}sigma_e {c |} {res} 1.4004196
            {txt}rho {c |} {res}  .6008852{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est4
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist  $year_NIGERIA if country==2, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    15,063
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     7,154

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0466{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.1312{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.1055{col 63}{txt}max{col 67}={col 69}{res}         4

{txt}{col 49}F({res}18{txt},{res}7153{txt}){col 67}={col 70}{res}    19.89
{txt}corr(u_i, Xb){col 16}= {res}0.1136{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2} .1290158{col 29}{space 2}  .021262{col 40}{space 1}    6.07{col 49}{space 3}0.000{col 57}{space 4}  .087336{col 70}{space 3} .1706956
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2}-.0031836{col 29}{space 2} .0007413{col 40}{space 1}   -4.29{col 49}{space 3}0.000{col 57}{space 4}-.0046367{col 70}{space 3}-.0017305
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0317861{col 29}{space 2} .0098019{col 40}{space 1}    3.24{col 49}{space 3}0.001{col 57}{space 4} .0125714{col 70}{space 3} .0510008
{txt}dependent_share {c |}{col 17}{res}{space 2}  .174705{col 29}{space 2} .0884326{col 40}{space 1}    1.98{col 49}{space 3}0.048{col 57}{space 4}  .001351{col 70}{space 3}  .348059
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0025124{col 29}{space 2}   .00228{col 40}{space 1}   -1.10{col 49}{space 3}0.271{col 57}{space 4}-.0069819{col 70}{space 3} .0019571
{txt}{space 4}female_head {c |}{col 17}{res}{space 2}-.0144744{col 29}{space 2} .0814807{col 40}{space 1}   -0.18{col 49}{space 3}0.859{col 57}{space 4}-.1742007{col 70}{space 3} .1452519
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0362958{col 29}{space 2} .0395461{col 40}{space 1}    0.92{col 49}{space 3}0.359{col 57}{space 4}-.0412262{col 70}{space 3} .1138179
{txt}{space 7}motobike {c |}{col 17}{res}{space 2}-.0024425{col 29}{space 2}  .041622{col 40}{space 1}   -0.06{col 49}{space 3}0.953{col 57}{space 4}-.0840339{col 70}{space 3} .0791489
{txt}{space 10}phone {c |}{col 17}{res}{space 2}  .143373{col 29}{space 2} .0403692{col 40}{space 1}    3.55{col 49}{space 3}0.000{col 57}{space 4} .0642374{col 70}{space 3} .2225087
{txt}{space 4}electricity {c |}{col 17}{res}{space 2} .0889169{col 29}{space 2} .0488136{col 40}{space 1}    1.82{col 49}{space 3}0.069{col 57}{space 4}-.0067723{col 70}{space 3}  .184606
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .2273822{col 29}{space 2} .0568546{col 40}{space 1}    4.00{col 49}{space 3}0.000{col 57}{space 4} .1159304{col 70}{space 3}  .338834
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2739989{col 29}{space 2} .0430056{col 40}{space 1}    6.37{col 49}{space 3}0.000{col 57}{space 4} .1896952{col 70}{space 3} .3583027
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0390003{col 29}{space 2}  .059805{col 40}{space 1}    0.65{col 49}{space 3}0.514{col 57}{space 4}-.0782352{col 70}{space 3} .1562357
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0065014{col 29}{space 2} .0112932{col 40}{space 1}    0.58{col 49}{space 3}0.565{col 57}{space 4}-.0156366{col 70}{space 3} .0286394
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .2278597{col 29}{space 2} .1023441{col 40}{space 1}    2.23{col 49}{space 3}0.026{col 57}{space 4}  .027235{col 70}{space 3} .4284844
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.5735758{col 29}{space 2} .0555189{col 40}{space 1}  -10.33{col 49}{space 3}0.000{col 57}{space 4}-.6824093{col 70}{space 3}-.4647424
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.4902973{col 29}{space 2} .0551775{col 40}{space 1}   -8.89{col 49}{space 3}0.000{col 57}{space 4}-.5984615{col 70}{space 3} -.382133
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2}-.2990733{col 29}{space 2}  .055533{col 40}{space 1}   -5.39{col 49}{space 3}0.000{col 57}{space 4}-.4079344{col 70}{space 3}-.1902122
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.058261{col 29}{space 2} .2264761{col 40}{space 1}   22.33{col 49}{space 3}0.000{col 57}{space 4} 4.614301{col 70}{space 3} 5.502221
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.4736975
        {txt}sigma_e {c |} {res} 1.2207038
            {txt}rho {c |} {res} .59307548{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est5
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist  $year_TANZANIA if country==5, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    11,830
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     5,710

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0295{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.0872{col 63}{txt}avg{col 67}={col 69}{res}       2.1
{txt}     overall = {res}0.0711{col 63}{txt}max{col 67}={col 69}{res}         5

{txt}{col 49}F({res}18{txt},{res}5709{txt}){col 67}={col 70}{res}     9.90
{txt}corr(u_i, Xb){col 16}= {res}0.0395{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2}-.0189325{col 29}{space 2} .0263568{col 40}{space 1}   -0.72{col 49}{space 3}0.473{col 57}{space 4}-.0706018{col 70}{space 3} .0327368
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2}-.0048188{col 29}{space 2} .0023451{col 40}{space 1}   -2.05{col 49}{space 3}0.040{col 57}{space 4} -.009416{col 70}{space 3}-.0002215
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0293323{col 29}{space 2} .0110182{col 40}{space 1}    2.66{col 49}{space 3}0.008{col 57}{space 4} .0077325{col 70}{space 3} .0509322
{txt}dependent_share {c |}{col 17}{res}{space 2} .3903808{col 29}{space 2} .1094074{col 40}{space 1}    3.57{col 49}{space 3}0.000{col 57}{space 4} .1759007{col 70}{space 3} .6048609
{txt}{space 7}head_age {c |}{col 17}{res}{space 2}-.0095988{col 29}{space 2} .0035981{col 40}{space 1}   -2.67{col 49}{space 3}0.008{col 57}{space 4}-.0166524{col 70}{space 3}-.0025452
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0162198{col 29}{space 2} .1047731{col 40}{space 1}    0.15{col 49}{space 3}0.877{col 57}{space 4}-.1891752{col 70}{space 3} .2216148
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .0086422{col 29}{space 2} .0645448{col 40}{space 1}    0.13{col 49}{space 3}0.893{col 57}{space 4}  -.11789{col 70}{space 3} .1351744
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2536618{col 29}{space 2}  .086304{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} .0844732{col 70}{space 3} .4228505
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2678262{col 29}{space 2} .0488924{col 40}{space 1}    5.48{col 49}{space 3}0.000{col 57}{space 4} .1719784{col 70}{space 3} .3636739
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .104057{col 29}{space 2} .0572763{col 40}{space 1}    1.82{col 49}{space 3}0.069{col 57}{space 4}-.0082262{col 70}{space 3} .2163402
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .1041547{col 29}{space 2} .0389024{col 40}{space 1}    2.68{col 49}{space 3}0.007{col 57}{space 4} .0278913{col 70}{space 3} .1804181
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2}  .215305{col 29}{space 2} .0403813{col 40}{space 1}    5.33{col 49}{space 3}0.000{col 57}{space 4} .1361424{col 70}{space 3} .2944677
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2}-.0270389{col 29}{space 2} .0447045{col 40}{space 1}   -0.60{col 49}{space 3}0.545{col 57}{space 4}-.1146768{col 70}{space 3} .0605989
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0160811{col 29}{space 2} .0070001{col 40}{space 1}    2.30{col 49}{space 3}0.022{col 57}{space 4} .0023583{col 70}{space 3}  .029804
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0167171{col 29}{space 2} .0498295{col 40}{space 1}    0.34{col 49}{space 3}0.737{col 57}{space 4}-.0809677{col 70}{space 3} .1144019
{txt}{space 9}year_1 {c |}{col 17}{res}{space 2}-.1735623{col 29}{space 2} .0429291{col 40}{space 1}   -4.04{col 49}{space 3}0.000{col 57}{space 4}-.2577196{col 70}{space 3} -.089405
{txt}{space 9}year_5 {c |}{col 17}{res}{space 2}-.0955505{col 29}{space 2}   .03927{col 40}{space 1}   -2.43{col 49}{space 3}0.015{col 57}{space 4}-.1725346{col 70}{space 3}-.0185665
{txt}{space 9}year_7 {c |}{col 17}{res}{space 2} .1433052{col 29}{space 2} .0435629{col 40}{space 1}    3.29{col 49}{space 3}0.001{col 57}{space 4} .0579054{col 70}{space 3} .2287049
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 5.721371{col 29}{space 2} .2835099{col 40}{space 1}   20.18{col 49}{space 3}0.000{col 57}{space 4} 5.165584{col 70}{space 3} 6.277158
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.3253006
        {txt}sigma_e {c |} {res} 1.2278813
            {txt}rho {c |} {res} .53810056{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est6
{txt}
{com}. 
. 
. xtreg hdd9  pdd9_dist  sum_dist  $xlist  $year_UGANDA if country==4, cluster(HHID_panel)  fe
{res}
{txt}Fixed-effects (within) regression{col 49}Number of obs{col 67}={col 69}{res}    16,114
{txt}Group variable: {res}HHID_panel{txt}{col 49}Number of groups{col 67}={col 69}{res}     4,402

{txt}R-sq:{col 49}Obs per group:
     within  = {res}0.0446{col 63}{txt}min{col 67}={col 69}{res}         1
{txt}     between = {res}0.2211{col 63}{txt}avg{col 67}={col 69}{res}       3.7
{txt}     overall = {res}0.1464{col 63}{txt}max{col 67}={col 69}{res}         7

{txt}{col 49}F({res}20{txt},{res}4401{txt}){col 67}={col 70}{res}    24.87
{txt}corr(u_i, Xb){col 16}= {res}0.2187{txt}{col 49}Prob > F{col 67}={col 73}{res}0.0000

{txt}{ralign 81:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}           hdd9{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}pdd9_dist {c |}{col 17}{res}{space 2} .0031982{col 29}{space 2} .0176148{col 40}{space 1}    0.18{col 49}{space 3}0.856{col 57}{space 4}-.0313357{col 70}{space 3} .0377321
{txt}{space 7}sum_dist {c |}{col 17}{res}{space 2} .0040978{col 29}{space 2} .0018097{col 40}{space 1}    2.26{col 49}{space 3}0.024{col 57}{space 4} .0005499{col 70}{space 3} .0076457
{txt}{space 9}hhsize {c |}{col 17}{res}{space 2} .0221678{col 29}{space 2} .0090215{col 40}{space 1}    2.46{col 49}{space 3}0.014{col 57}{space 4} .0044811{col 70}{space 3} .0398545
{txt}dependent_share {c |}{col 17}{res}{space 2} .1102261{col 29}{space 2} .0824146{col 40}{space 1}    1.34{col 49}{space 3}0.181{col 57}{space 4} -.051348{col 70}{space 3} .2718002
{txt}{space 7}head_age {c |}{col 17}{res}{space 2} .0058894{col 29}{space 2} .0028553{col 40}{space 1}    2.06{col 49}{space 3}0.039{col 57}{space 4} .0002916{col 70}{space 3} .0114873
{txt}{space 4}female_head {c |}{col 17}{res}{space 2} .0539293{col 29}{space 2} .0674025{col 40}{space 1}    0.80{col 49}{space 3}0.424{col 57}{space 4}-.0782134{col 70}{space 3}  .186072
{txt}{space 6}head_read {c |}{col 17}{res}{space 2} .1997388{col 29}{space 2} .0475661{col 40}{space 1}    4.20{col 49}{space 3}0.000{col 57}{space 4} .1064853{col 70}{space 3} .2929923
{txt}{space 7}motobike {c |}{col 17}{res}{space 2} .2437116{col 29}{space 2} .0564989{col 40}{space 1}    4.31{col 49}{space 3}0.000{col 57}{space 4} .1329453{col 70}{space 3} .3544778
{txt}{space 10}phone {c |}{col 17}{res}{space 2} .2493958{col 29}{space 2} .0378479{col 40}{space 1}    6.59{col 49}{space 3}0.000{col 57}{space 4} .1751949{col 70}{space 3} .3235967
{txt}{space 4}electricity {c |}{col 17}{res}{space 2}  .319811{col 29}{space 2} .0388545{col 40}{space 1}    8.23{col 49}{space 3}0.000{col 57}{space 4} .2436366{col 70}{space 3} .3959854
{txt}{space 8}wagejob {c |}{col 17}{res}{space 2} .0465696{col 29}{space 2} .0308034{col 40}{space 1}    1.51{col 49}{space 3}0.131{col 57}{space 4}-.0138206{col 70}{space 3} .1069599
{txt}{space 5}enterprise {c |}{col 17}{res}{space 2} .2140903{col 29}{space 2} .0322563{col 40}{space 1}    6.64{col 49}{space 3}0.000{col 57}{space 4} .1508517{col 70}{space 3} .2773289
{txt}{space 2}weather_shock {c |}{col 17}{res}{space 2} .0525313{col 29}{space 2} .0280261{col 40}{space 1}    1.87{col 49}{space 3}0.061{col 57}{space 4}-.0024139{col 70}{space 3} .1074764
{txt}{space 6}plot_area {c |}{col 17}{res}{space 2} .0005565{col 29}{space 2} .0015425{col 40}{space 1}    0.36{col 49}{space 3}0.718{col 57}{space 4}-.0024676{col 70}{space 3} .0035806
{txt}{space 5}other_crop {c |}{col 17}{res}{space 2} .0598243{col 29}{space 2} .0369315{col 40}{space 1}    1.62{col 49}{space 3}0.105{col 57}{space 4}  -.01258{col 70}{space 3} .1322286
{txt}{space 9}year_3 {c |}{col 17}{res}{space 2}-.1171589{col 29}{space 2} .0405037{col 40}{space 1}   -2.89{col 49}{space 3}0.004{col 57}{space 4}-.1965665{col 70}{space 3}-.0377512
{txt}{space 9}year_4 {c |}{col 17}{res}{space 2}-.0091675{col 29}{space 2}  .037111{col 40}{space 1}   -0.25{col 49}{space 3}0.805{col 57}{space 4}-.0819236{col 70}{space 3} .0635887
{txt}{space 9}year_6 {c |}{col 17}{res}{space 2} .3316319{col 29}{space 2} .0366819{col 40}{space 1}    9.04{col 49}{space 3}0.000{col 57}{space 4}  .259717{col 70}{space 3} .4035468
{txt}{space 9}year_8 {c |}{col 17}{res}{space 2} .0632438{col 29}{space 2} .0366361{col 40}{space 1}    1.73{col 49}{space 3}0.084{col 57}{space 4}-.0085814{col 70}{space 3}  .135069
{txt}{space 8}year_10 {c |}{col 17}{res}{space 2} .2513223{col 29}{space 2} .0332964{col 40}{space 1}    7.55{col 49}{space 3}0.000{col 57}{space 4} .1860447{col 70}{space 3} .3165999
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 4.316654{col 29}{space 2} .2050433{col 40}{space 1}   21.05{col 49}{space 3}0.000{col 57}{space 4} 3.914666{col 70}{space 3} 4.718642
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
        sigma_u {c |} {res} 1.2174327
        {txt}sigma_e {c |} {res} 1.2676197
            {txt}rho {c |} {res} .47981266{txt}   (fraction of variance due to u_i)
{hline 16}{c BT}{hline 64}

{com}. eststo est7
{txt}
{com}. esttab using  S27_fe.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) 
{res}{txt}(note: file S27_fe.rtf not found)
(output written to {browse  `"S27_fe.rtf"'})

{com}. restore
{txt}
{com}. 
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. *                                 Poisson CRE                                  *
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. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop hdd9 pdd9 no_species{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. global xlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop  motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean  
{txt}
{com}. 
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. ********************************************************************************
. *                                   S20                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. poisson hdd9  no_species   $xlist  no_species_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-177983.89}  
Iteration 1:{space 3}log pseudolikelihood = {res:-177983.88}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 49}Wald chi2({res}35{txt}){col 67}= {res}  24429.45
{txt}Log pseudolikelihood = {res}-177983.88{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0080444{col 30}{space 2} .0005259{col 41}{space 1}   15.30{col 50}{space 3}0.000{col 58}{space 4} .0070136{col 71}{space 3} .0090751
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0010985{col 30}{space 2} .0004067{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4}-.0018956{col 71}{space 3}-.0003014
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .010206{col 30}{space 2} .0045568{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0012748{col 71}{space 3} .0191371
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000633{col 30}{space 2} .0000762{col 41}{space 1}    0.83{col 50}{space 3}0.406{col 58}{space 4}-.0000861{col 71}{space 3} .0002127
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0135469{col 30}{space 2} .0026595{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .0083343{col 71}{space 3} .0187595
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0666869{col 30}{space 2}  .002607{col 41}{space 1}   25.58{col 50}{space 3}0.000{col 58}{space 4} .0615772{col 71}{space 3} .0717966
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .019741{col 30}{space 2} .0041385{col 41}{space 1}    4.77{col 50}{space 3}0.000{col 58}{space 4} .0116297{col 71}{space 3} .0278523
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0427138{col 30}{space 2} .0032549{col 41}{space 1}   13.12{col 50}{space 3}0.000{col 58}{space 4} .0363343{col 71}{space 3} .0490933
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0320606{col 30}{space 2} .0034371{col 41}{space 1}    9.33{col 50}{space 3}0.000{col 58}{space 4}  .025324{col 71}{space 3} .0387972
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .022117{col 30}{space 2}  .002877{col 41}{space 1}    7.69{col 50}{space 3}0.000{col 58}{space 4} .0164781{col 71}{space 3} .0277559
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0387712{col 30}{space 2} .0027339{col 41}{space 1}   14.18{col 50}{space 3}0.000{col 58}{space 4} .0334129{col 71}{space 3} .0441296
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0269126{col 30}{space 2} .0024899{col 41}{space 1}  -10.81{col 50}{space 3}0.000{col 58}{space 4}-.0317927{col 71}{space 3}-.0220326
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0000157{col 30}{space 2} .0001888{col 41}{space 1}   -0.08{col 50}{space 3}0.934{col 58}{space 4}-.0003858{col 71}{space 3} .0003543
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0166665{col 30}{space 2} .0030809{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4}  .010628{col 71}{space 3} .0227049
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0063951{col 30}{space 2} .0056039{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4}-.0045883{col 71}{space 3} .0173786
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1074814{col 30}{space 2}  .004815{col 41}{space 1}   22.32{col 50}{space 3}0.000{col 58}{space 4} .0980441{col 71}{space 3} .1169187
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1140868{col 30}{space 2} .0046862{col 41}{space 1}   24.35{col 50}{space 3}0.000{col 58}{space 4}  .104902{col 71}{space 3} .1232717
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0351424{col 30}{space 2} .0042191{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .0268731{col 71}{space 3} .0434117
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0328609{col 30}{space 2} .0039172{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .0251833{col 71}{space 3} .0405384
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0034825{col 30}{space 2} .0006478{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}-.0047521{col 71}{space 3}-.0022128
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.074964{col 30}{space 2}  .005297{col 41}{space 1}  -14.15{col 50}{space 3}0.000{col 58}{space 4}-.0853459{col 71}{space 3} -.064582
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.2839706{col 30}{space 2} .0056926{col 41}{space 1}  -49.88{col 50}{space 3}0.000{col 58}{space 4}-.2951279{col 71}{space 3}-.2728134
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.0776484{col 30}{space 2} .0052222{col 41}{space 1}  -14.87{col 50}{space 3}0.000{col 58}{space 4}-.0878836{col 71}{space 3}-.0674131
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.0463424{col 30}{space 2} .0049301{col 41}{space 1}   -9.40{col 50}{space 3}0.000{col 58}{space 4}-.0560053{col 71}{space 3}-.0366796
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1024175{col 30}{space 2} .0058101{col 41}{space 1}   17.63{col 50}{space 3}0.000{col 58}{space 4} .0910299{col 71}{space 3} .1138051
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0588649{col 30}{space 2} .0072071{col 41}{space 1}   -8.17{col 50}{space 3}0.000{col 58}{space 4}-.0729906{col 71}{space 3}-.0447392
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0217542{col 30}{space 2} .0049185{col 41}{space 1}   -4.42{col 50}{space 3}0.000{col 58}{space 4}-.0313943{col 71}{space 3}-.0121141
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0198043{col 30}{space 2} .0058422{col 41}{space 1}   -3.39{col 50}{space 3}0.001{col 58}{space 4}-.0312548{col 71}{space 3}-.0083539
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0090922{col 30}{space 2} .0049582{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.0188101{col 71}{space 3} .0006258
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}-.0057535{col 30}{space 2} .0056889{col 41}{space 1}   -1.01{col 50}{space 3}0.312{col 58}{space 4}-.0169036{col 71}{space 3} .0053965
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.037602{col 30}{space 2} .0056304{col 41}{space 1}   -6.68{col 50}{space 3}0.000{col 58}{space 4}-.0486374{col 71}{space 3}-.0265665
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0132387{col 30}{space 2} .0054502{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0025566{col 71}{space 3} .0239209
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0528862{col 30}{space 2} .0072353{col 41}{space 1}   -7.31{col 50}{space 3}0.000{col 58}{space 4}-.0670671{col 71}{space 3}-.0387053
{txt}{space 11}2018  {c |}{col 18}{res}{space 2}  .052873{col 30}{space 2} .0057617{col 41}{space 1}    9.18{col 50}{space 3}0.000{col 58}{space 4} .0415803{col 71}{space 3} .0641657
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0407237{col 30}{space 2} .0052973{col 41}{space 1}   -7.69{col 50}{space 3}0.000{col 58}{space 4}-.0511063{col 71}{space 3}-.0303411
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.538139{col 30}{space 2} .0083627{col 41}{space 1}  183.93{col 50}{space 3}0.000{col 58}{space 4} 1.521749{col 71}{space 3}  1.55453
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0455606{col 30}{space 2}  .002977{col 41}{space 1}   15.30{col 50}{space 3}0.000{col 58}{space 4} .0397258{col 71}{space 3} .0513954
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0062215{col 30}{space 2} .0023034{col 41}{space 1}   -2.70{col 50}{space 3}0.007{col 58}{space 4} -.010736{col 71}{space 3}-.0017071
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0578034{col 30}{space 2} .0258071{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0072224{col 71}{space 3} .1083844
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0003585{col 30}{space 2} .0004317{col 41}{space 1}    0.83{col 50}{space 3}0.406{col 58}{space 4}-.0004876{col 71}{space 3} .0012047
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .076725{col 30}{space 2} .0150618{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .0472044{col 71}{space 3} .1062456
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3776925{col 30}{space 2} .0147652{col 41}{space 1}   25.58{col 50}{space 3}0.000{col 58}{space 4} .3487532{col 71}{space 3} .4066318
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1118065{col 30}{space 2} .0234383{col 41}{space 1}    4.77{col 50}{space 3}0.000{col 58}{space 4} .0658683{col 71}{space 3} .1577448
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2419167{col 30}{space 2}  .018434{col 41}{space 1}   13.12{col 50}{space 3}0.000{col 58}{space 4} .2057868{col 71}{space 3} .2780466
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1815809{col 30}{space 2} .0194667{col 41}{space 1}    9.33{col 50}{space 3}0.000{col 58}{space 4} .1434269{col 71}{space 3} .2197348
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1252633{col 30}{space 2} .0162947{col 41}{space 1}    7.69{col 50}{space 3}0.000{col 58}{space 4} .0933263{col 71}{space 3} .1572004
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2195874{col 30}{space 2} .0154836{col 41}{space 1}   14.18{col 50}{space 3}0.000{col 58}{space 4} .1892402{col 71}{space 3} .2499346
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1524243{col 30}{space 2} .0141018{col 41}{space 1}  -10.81{col 50}{space 3}0.000{col 58}{space 4}-.1800633{col 71}{space 3}-.1247853
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0000891{col 30}{space 2} .0010694{col 41}{space 1}   -0.08{col 50}{space 3}0.934{col 58}{space 4}-.0021851{col 71}{space 3} .0020069
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0943933{col 30}{space 2} .0174498{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .0601922{col 71}{space 3} .1285944
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0362199{col 30}{space 2} .0317383{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4}-.0259861{col 71}{space 3} .0984259
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6087392{col 30}{space 2} .0272482{col 41}{space 1}   22.34{col 50}{space 3}0.000{col 58}{space 4} .5553337{col 71}{space 3} .6621447
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6461502{col 30}{space 2} .0265196{col 41}{space 1}   24.36{col 50}{space 3}0.000{col 58}{space 4} .5941726{col 71}{space 3} .6981277
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1990349{col 30}{space 2} .0238967{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .1521981{col 71}{space 3} .2458716
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .186113{col 30}{space 2} .0221837{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .1426337{col 71}{space 3} .2295923
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0197235{col 30}{space 2} .0036688{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}-.0269143{col 71}{space 3}-.0125327
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4395754{col 30}{space 2} .0315084{col 41}{space 1}  -13.95{col 50}{space 3}0.000{col 58}{space 4}-.5013307{col 71}{space 3}  -.37782
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.504616{col 30}{space 2} .0312141{col 41}{space 1}  -48.20{col 50}{space 3}0.000{col 58}{space 4}-1.565794{col 71}{space 3}-1.443437
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4547134{col 30}{space 2} .0310686{col 41}{space 1}  -14.64{col 50}{space 3}0.000{col 58}{space 4}-.5156067{col 71}{space 3}-.3938201
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2756208{col 30}{space 2} .0296788{col 41}{space 1}   -9.29{col 50}{space 3}0.000{col 58}{space 4}-.3337903{col 71}{space 3}-.2174514
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6563886{col 30}{space 2} .0370036{col 41}{space 1}   17.74{col 50}{space 3}0.000{col 58}{space 4} .5838628{col 71}{space 3} .7289143
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.3278195{col 30}{space 2} .0400301{col 41}{space 1}   -8.19{col 50}{space 3}0.000{col 58}{space 4}-.4062771{col 71}{space 3}-.2493618
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.1234031{col 30}{space 2} .0281164{col 41}{space 1}   -4.39{col 50}{space 3}0.000{col 58}{space 4}-.1785103{col 71}{space 3}-.0682959
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.1124515{col 30}{space 2} .0332958{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4}-.1777101{col 71}{space 3}-.0471929
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0519029{col 30}{space 2} .0283832{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4} -.107533{col 71}{space 3} .0037272
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}-.0328991{col 30}{space 2} .0325715{col 41}{space 1}   -1.01{col 50}{space 3}0.312{col 58}{space 4} -.096738{col 71}{space 3} .0309398
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2116259{col 30}{space 2} .0318974{col 41}{space 1}   -6.63{col 50}{space 3}0.000{col 58}{space 4}-.2741437{col 71}{space 3}-.1491081
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0764227{col 30}{space 2} .0313467{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .0149842{col 71}{space 3} .1378611
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2953977{col 30}{space 2}  .040303{col 41}{space 1}   -7.33{col 50}{space 3}0.000{col 58}{space 4}-.3743902{col 71}{space 3}-.2164052
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3113606{col 30}{space 2} .0335939{col 41}{space 1}    9.27{col 50}{space 3}0.000{col 58}{space 4} .2455178{col 71}{space 3} .3772034
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.2288401{col 30}{space 2} .0301098{col 41}{space 1}   -7.60{col 50}{space 3}0.000{col 58}{space 4}-.2878541{col 71}{space 3} -.169826
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. 
. poisson hdd9  no_species   $xlist  no_species_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -25102.96}  
Iteration 1:{space 3}log pseudolikelihood = {res: -25102.96}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    13,511
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   3478.30
{txt}Log pseudolikelihood = {res} -25102.96{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0026525{col 30}{space 2} .0013128{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0000794{col 71}{space 3} .0052255
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0112439{col 30}{space 2} .0016129{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .0080826{col 71}{space 3} .0144052
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0039824{col 30}{space 2} .0132019{col 41}{space 1}   -0.30{col 50}{space 3}0.763{col 58}{space 4}-.0298576{col 71}{space 3} .0218928
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0009271{col 30}{space 2} .0002253{col 41}{space 1}   -4.12{col 50}{space 3}0.000{col 58}{space 4}-.0013686{col 71}{space 3}-.0004856
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0025009{col 30}{space 2} .0076804{col 41}{space 1}    0.33{col 50}{space 3}0.745{col 58}{space 4}-.0125524{col 71}{space 3} .0175543
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1026582{col 30}{space 2} .0071983{col 41}{space 1}   14.26{col 50}{space 3}0.000{col 58}{space 4} .0885498{col 71}{space 3} .1167666
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0261657{col 30}{space 2} .0251154{col 41}{space 1}   -1.04{col 50}{space 3}0.297{col 58}{space 4}-.0753911{col 71}{space 3} .0230596
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0453104{col 30}{space 2} .0086047{col 41}{space 1}    5.27{col 50}{space 3}0.000{col 58}{space 4} .0284455{col 71}{space 3} .0621753
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0402388{col 30}{space 2} .0102658{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .0201183{col 71}{space 3} .0603594
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.007128{col 30}{space 2} .0107324{col 41}{space 1}   -0.66{col 50}{space 3}0.507{col 58}{space 4}-.0281632{col 71}{space 3} .0139073
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0462608{col 30}{space 2} .0104677{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .0257445{col 71}{space 3} .0667771
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0669527{col 30}{space 2} .0078764{col 41}{space 1}   -8.50{col 50}{space 3}0.000{col 58}{space 4}-.0823901{col 71}{space 3}-.0515153
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0015386{col 30}{space 2} .0008527{col 41}{space 1}    1.80{col 50}{space 3}0.071{col 58}{space 4}-.0001326{col 71}{space 3} .0032098
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0710118{col 30}{space 2} .0083304{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4} .0546846{col 71}{space 3} .0873391
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .192041{col 30}{space 2} .0384954{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .1165914{col 71}{space 3} .2674906
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1139525{col 30}{space 2} .0129657{col 41}{space 1}    8.79{col 50}{space 3}0.000{col 58}{space 4} .0885401{col 71}{space 3} .1393649
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1231819{col 30}{space 2} .0150649{col 41}{space 1}    8.18{col 50}{space 3}0.000{col 58}{space 4} .0936553{col 71}{space 3} .1527084
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .100233{col 30}{space 2} .0160132{col 41}{space 1}    6.26{col 50}{space 3}0.000{col 58}{space 4} .0688477{col 71}{space 3} .1316183
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0189331{col 30}{space 2} .0131527{col 41}{space 1}    1.44{col 50}{space 3}0.150{col 58}{space 4}-.0068457{col 71}{space 3} .0447119
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0011285{col 30}{space 2} .0016086{col 41}{space 1}    0.70{col 50}{space 3}0.483{col 58}{space 4}-.0020243{col 71}{space 3} .0042813
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0402406{col 30}{space 2} .0049215{col 41}{space 1}   -8.18{col 50}{space 3}0.000{col 58}{space 4}-.0498866{col 71}{space 3}-.0305946
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.213279{col 30}{space 2} .0156244{col 41}{space 1}   77.65{col 50}{space 3}0.000{col 58}{space 4} 1.182656{col 71}{space 3} 1.243903
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    13,511
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0117364{col 30}{space 2} .0058081{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0003527{col 71}{space 3} .0231202
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0497508{col 30}{space 2} .0071377{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4}  .035761{col 71}{space 3} .0637405
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0176209{col 30}{space 2} .0584132{col 41}{space 1}   -0.30{col 50}{space 3}0.763{col 58}{space 4}-.1321086{col 71}{space 3} .0968668
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0041022{col 30}{space 2} .0009968{col 41}{space 1}   -4.12{col 50}{space 3}0.000{col 58}{space 4}-.0060559{col 71}{space 3}-.0021485
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0110659{col 30}{space 2} .0339834{col 41}{space 1}    0.33{col 50}{space 3}0.745{col 58}{space 4}-.0555403{col 71}{space 3} .0776721
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4542309{col 30}{space 2} .0318831{col 41}{space 1}   14.25{col 50}{space 3}0.000{col 58}{space 4} .3917411{col 71}{space 3} .5167206
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1157753{col 30}{space 2} .1111291{col 41}{space 1}   -1.04{col 50}{space 3}0.298{col 58}{space 4}-.3335844{col 71}{space 3} .1020337
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2004846{col 30}{space 2} .0380776{col 41}{space 1}    5.27{col 50}{space 3}0.000{col 58}{space 4} .1258538{col 71}{space 3} .2751153
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1780445{col 30}{space 2} .0454146{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .0890335{col 71}{space 3} .2670554
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.031539{col 30}{space 2} .0474892{col 41}{space 1}   -0.66{col 50}{space 3}0.507{col 58}{space 4}-.1246162{col 71}{space 3} .0615382
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2046897{col 30}{space 2} .0463141{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1139158{col 71}{space 3} .2954636
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.296245{col 30}{space 2} .0348463{col 41}{space 1}   -8.50{col 50}{space 3}0.000{col 58}{space 4}-.3645426{col 71}{space 3}-.2279474
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0068079{col 30}{space 2} .0037724{col 41}{space 1}    1.80{col 50}{space 3}0.071{col 58}{space 4} -.000586{col 71}{space 3} .0142017
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3142053{col 30}{space 2} .0368874{col 41}{space 1}    8.52{col 50}{space 3}0.000{col 58}{space 4} .2419073{col 71}{space 3} .3865032
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .849722{col 30}{space 2} .1703349{col 41}{space 1}    4.99{col 50}{space 3}0.000{col 58}{space 4} .5158717{col 71}{space 3} 1.183572
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5042047{col 30}{space 2} .0574034{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .3916961{col 71}{space 3} .6167134
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5450417{col 30}{space 2} .0666824{col 41}{space 1}    8.17{col 50}{space 3}0.000{col 58}{space 4} .4143465{col 71}{space 3} .6757368
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4435001{col 30}{space 2} .0708066{col 41}{space 1}    6.26{col 50}{space 3}0.000{col 58}{space 4} .3047217{col 71}{space 3} .5822786
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0837732{col 30}{space 2} .0581901{col 41}{space 1}    1.44{col 50}{space 3}0.150{col 58}{space 4}-.0302774{col 71}{space 3} .1978238
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} .0049934{col 30}{space 2} .0071177{col 41}{space 1}    0.70{col 50}{space 3}0.483{col 58}{space 4} -.008957{col 71}{space 3} .0189438
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1780521{col 30}{space 2} .0217557{col 41}{space 1}   -8.18{col 50}{space 3}0.000{col 58}{space 4}-.2206926{col 71}{space 3}-.1354116
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  no_species   $xlist  no_species_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -18447.41}  
Iteration 1:{space 3}log pseudolikelihood = {res: -18447.41}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     9,163
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   3268.15
{txt}Log pseudolikelihood = {res} -18447.41{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0149962{col 30}{space 2}  .001627{col 41}{space 1}    9.22{col 50}{space 3}0.000{col 58}{space 4} .0118073{col 71}{space 3} .0181851
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0027672{col 30}{space 2} .0015205{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4}-.0057473{col 71}{space 3} .0002129
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0551975{col 30}{space 2} .0124068{col 41}{space 1}   -4.45{col 50}{space 3}0.000{col 58}{space 4}-.0795144{col 71}{space 3}-.0308805
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0005897{col 30}{space 2}  .000218{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4} -.001017{col 71}{space 3}-.0001625
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0165376{col 30}{space 2} .0072472{col 41}{space 1}   -2.28{col 50}{space 3}0.022{col 58}{space 4}-.0307419{col 71}{space 3}-.0023333
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0592106{col 30}{space 2}   .00821{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .0431192{col 71}{space 3} .0753019
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0318718{col 30}{space 2} .0195058{col 41}{space 1}    1.63{col 50}{space 3}0.102{col 58}{space 4}-.0063588{col 71}{space 3} .0701025
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0430522{col 30}{space 2} .0088405{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0257251{col 71}{space 3} .0603793
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0626406{col 30}{space 2} .0121065{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .0389124{col 71}{space 3} .0863688
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0288843{col 30}{space 2}  .008836{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0115662{col 71}{space 3} .0462025
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0414626{col 30}{space 2}  .006548{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .0286287{col 71}{space 3} .0542964
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0383428{col 30}{space 2} .0056029{col 41}{space 1}   -6.84{col 50}{space 3}0.000{col 58}{space 4}-.0493243{col 71}{space 3}-.0273612
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0020957{col 30}{space 2} .0041761{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0060893{col 71}{space 3} .0102808
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0134256{col 30}{space 2} .0084048{col 41}{space 1}   -1.60{col 50}{space 3}0.110{col 58}{space 4}-.0298988{col 71}{space 3} .0030476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0417881{col 30}{space 2} .0306388{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0182628{col 71}{space 3} .1018389
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0849568{col 30}{space 2}  .012809{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .0598515{col 71}{space 3}  .110062
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0945174{col 30}{space 2} .0155718{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .0639973{col 71}{space 3} .1250376
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0590435{col 30}{space 2} .0121981{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .0351357{col 71}{space 3} .0829514
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0577178{col 30}{space 2} .0107567{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .0366351{col 71}{space 3} .0788005
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0079661{col 30}{space 2} .0022355{col 41}{space 1}   -3.56{col 50}{space 3}0.000{col 58}{space 4}-.0123477{col 71}{space 3}-.0035846
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0179195{col 30}{space 2} .0068861{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4}  .004423{col 71}{space 3} .0314161
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0110389{col 30}{space 2} .0056915{col 41}{space 1}    1.94{col 50}{space 3}0.052{col 58}{space 4}-.0001162{col 71}{space 3}  .022194
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.667261{col 30}{space 2} .0147988{col 41}{space 1}  112.66{col 50}{space 3}0.000{col 58}{space 4} 1.638256{col 71}{space 3} 1.696266
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     9,163
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2}  .093594{col 30}{space 2} .0101458{col 41}{space 1}    9.22{col 50}{space 3}0.000{col 58}{space 4} .0737086{col 71}{space 3} .1134794
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0172708{col 30}{space 2} .0094864{col 41}{space 1}   -1.82{col 50}{space 3}0.069{col 58}{space 4}-.0358637{col 71}{space 3} .0013222
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3444979{col 30}{space 2} .0774827{col 41}{space 1}   -4.45{col 50}{space 3}0.000{col 58}{space 4}-.4963612{col 71}{space 3}-.1926345
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0036807{col 30}{space 2}   .00136{col 41}{space 1}   -2.71{col 50}{space 3}0.007{col 58}{space 4}-.0063463{col 71}{space 3}-.0010152
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1032143{col 30}{space 2} .0452151{col 41}{space 1}   -2.28{col 50}{space 3}0.022{col 58}{space 4}-.1918342{col 71}{space 3}-.0145943
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3695442{col 30}{space 2} .0512007{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .2691926{col 71}{space 3} .4698958
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1989181{col 30}{space 2} .1217408{col 41}{space 1}    1.63{col 50}{space 3}0.102{col 58}{space 4}-.0396895{col 71}{space 3} .4375257
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2686969{col 30}{space 2} .0551735{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1605588{col 71}{space 3}  .376835
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3909518{col 30}{space 2}  .075523{col 41}{space 1}    5.18{col 50}{space 3}0.000{col 58}{space 4} .2429295{col 71}{space 3} .5389741
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1802724{col 30}{space 2} .0551501{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0721802{col 71}{space 3} .2883647
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2587756{col 30}{space 2}  .040842{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .1787266{col 71}{space 3} .3388245
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2393045{col 30}{space 2} .0349634{col 41}{space 1}   -6.84{col 50}{space 3}0.000{col 58}{space 4}-.3078314{col 71}{space 3}-.1707776
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0130799{col 30}{space 2} .0260654{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0380074{col 71}{space 3} .0641672
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0837918{col 30}{space 2}  .052457{col 41}{space 1}   -1.60{col 50}{space 3}0.110{col 58}{space 4}-.1866056{col 71}{space 3} .0190221
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2608072{col 30}{space 2} .1912011{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.1139401{col 71}{space 3} .6355545
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5302312{col 30}{space 2} .0799659{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .3735008{col 71}{space 3} .6869615
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5899011{col 30}{space 2} .0971009{col 41}{space 1}    6.08{col 50}{space 3}0.000{col 58}{space 4} .3995869{col 71}{space 3} .7802153
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3685018{col 30}{space 2} .0760855{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4}  .219377{col 71}{space 3} .5176265
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3602276{col 30}{space 2} .0671349{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .2286456{col 71}{space 3} .4918095
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0497182{col 30}{space 2} .0139565{col 41}{space 1}   -3.56{col 50}{space 3}0.000{col 58}{space 4}-.0770723{col 71}{space 3} -.022364
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .1118391{col 30}{space 2} .0429708{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4}  .027618{col 71}{space 3} .1960603
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0688957{col 30}{space 2} .0355233{col 41}{space 1}    1.94{col 50}{space 3}0.052{col 58}{space 4}-.0007288{col 71}{space 3} .1385201
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. 
. poisson hdd9  no_species   $xlist  no_species_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-14084.395}  
Iteration 1:{space 3}log pseudolikelihood = {res:-14084.395}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     7,046
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   1619.89
{txt}Log pseudolikelihood = {res}-14084.395{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0256548{col 30}{space 2}  .003225{col 41}{space 1}    7.95{col 50}{space 3}0.000{col 58}{space 4} .0193339{col 71}{space 3} .0319757
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0028758{col 30}{space 2} .0011161{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .0006883{col 71}{space 3} .0050633
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0089569{col 30}{space 2} .0170702{col 41}{space 1}   -0.52{col 50}{space 3}0.600{col 58}{space 4}-.0424139{col 71}{space 3} .0245001
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004954{col 30}{space 2} .0002517{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} 2.13e-06{col 71}{space 3} .0009888
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .017042{col 30}{space 2} .0101922{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0029344{col 71}{space 3} .0370184
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0606412{col 30}{space 2} .0075869{col 41}{space 1}    7.99{col 50}{space 3}0.000{col 58}{space 4}  .045771{col 71}{space 3} .0755113
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0396449{col 30}{space 2} .0155925{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0090841{col 71}{space 3} .0702056
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0160004{col 30}{space 2} .0135705{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0105973{col 71}{space 3} .0425982
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0369363{col 30}{space 2} .0174404{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0027537{col 71}{space 3} .0711189
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0343557{col 30}{space 2} .0143806{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0061702{col 71}{space 3} .0625412
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0350909{col 30}{space 2} .0118255{col 41}{space 1}   -2.97{col 50}{space 3}0.003{col 58}{space 4}-.0582684{col 71}{space 3}-.0119134
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0290022{col 30}{space 2} .0085121{col 41}{space 1}   -3.41{col 50}{space 3}0.001{col 58}{space 4}-.0456856{col 71}{space 3}-.0123188
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004103{col 30}{space 2} .0003033{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4}-.0010049{col 71}{space 3} .0001842
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0290625{col 30}{space 2} .0375049{col 41}{space 1}    0.77{col 50}{space 3}0.438{col 58}{space 4}-.0444458{col 71}{space 3} .1025709
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0148812{col 30}{space 2} .0191572{col 41}{space 1}    0.78{col 50}{space 3}0.437{col 58}{space 4}-.0226662{col 71}{space 3} .0524286
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .065367{col 30}{space 2}  .016762{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0325142{col 71}{space 3} .0982199
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0789405{col 30}{space 2}  .020405{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0389474{col 71}{space 3} .1189336
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0314768{col 30}{space 2} .0176881{col 41}{space 1}    1.78{col 50}{space 3}0.075{col 58}{space 4}-.0031912{col 71}{space 3} .0661448
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0840569{col 30}{space 2}   .01456{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .0555198{col 71}{space 3}  .112594
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0284452{col 30}{space 2} .0036835{col 41}{space 1}   -7.72{col 50}{space 3}0.000{col 58}{space 4}-.0356648{col 71}{space 3}-.0212257
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0421451{col 30}{space 2} .0064319{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4} .0295388{col 71}{space 3} .0547513
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.537124{col 30}{space 2} .0192901{col 41}{space 1}   79.68{col 50}{space 3}0.000{col 58}{space 4} 1.499317{col 71}{space 3} 1.574932
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     7,046
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .1463374{col 30}{space 2} .0183692{col 41}{space 1}    7.97{col 50}{space 3}0.000{col 58}{space 4} .1103345{col 71}{space 3} .1823404
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0164038{col 30}{space 2} .0063648{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4}  .003929{col 71}{space 3} .0288787
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0510909{col 30}{space 2} .0973776{col 41}{space 1}   -0.52{col 50}{space 3}0.600{col 58}{space 4}-.2419474{col 71}{space 3} .1397657
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0028261{col 30}{space 2} .0014355{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0000124{col 71}{space 3} .0056397
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0972092{col 30}{space 2} .0581371{col 41}{space 1}    1.67{col 50}{space 3}0.095{col 58}{space 4}-.0167374{col 71}{space 3} .2111558
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3459025{col 30}{space 2} .0432387{col 41}{space 1}    8.00{col 50}{space 3}0.000{col 58}{space 4} .2611561{col 71}{space 3} .4306488
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2261379{col 30}{space 2} .0889224{col 41}{space 1}    2.54{col 50}{space 3}0.011{col 58}{space 4} .0518532{col 71}{space 3} .4004227
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0912679{col 30}{space 2} .0774011{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0604354{col 71}{space 3} .2429713
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2106878{col 30}{space 2} .0994725{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0157252{col 71}{space 3} .4056503
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1959678{col 30}{space 2} .0820284{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4}  .035195{col 71}{space 3} .3567405
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.2001615{col 30}{space 2} .0674261{col 41}{space 1}   -2.97{col 50}{space 3}0.003{col 58}{space 4}-.3323143{col 71}{space 3}-.0680087
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1654313{col 30}{space 2} .0485612{col 41}{space 1}   -3.41{col 50}{space 3}0.001{col 58}{space 4}-.2606095{col 71}{space 3} -.070253
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0023405{col 30}{space 2} .0017304{col 41}{space 1}   -1.35{col 50}{space 3}0.176{col 58}{space 4} -.005732{col 71}{space 3}  .001051
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1657753{col 30}{space 2} .2139298{col 41}{space 1}    0.77{col 50}{space 3}0.438{col 58}{space 4}-.2535195{col 71}{space 3}   .58507
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0848838{col 30}{space 2} .1092746{col 41}{space 1}    0.78{col 50}{space 3}0.437{col 58}{space 4}-.1292905{col 71}{space 3} .2990582
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3728594{col 30}{space 2} .0955967{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .1854932{col 71}{space 3} .5602255
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4502834{col 30}{space 2} .1163723{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .2221979{col 71}{space 3} .6783689
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1795462{col 30}{space 2} .1008785{col 41}{space 1}    1.78{col 50}{space 3}0.075{col 58}{space 4} -.018172{col 71}{space 3} .3772645
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4794679{col 30}{space 2} .0829468{col 41}{space 1}    5.78{col 50}{space 3}0.000{col 58}{space 4} .3168952{col 71}{space 3} .6420406
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2} -.162254{col 30}{space 2} .0209883{col 41}{space 1}   -7.73{col 50}{space 3}0.000{col 58}{space 4}-.2033903{col 71}{space 3}-.1211176
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2403991{col 30}{space 2} .0365894{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .1686851{col 71}{space 3} .3121131
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  no_species   $xlist  no_species_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37269.986}  
Iteration 1:{space 3}log pseudolikelihood = {res:-37269.986}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    18,592
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   4610.29
{txt}Log pseudolikelihood = {res}-37269.986{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0082871{col 30}{space 2} .0014475{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} .0054501{col 71}{space 3} .0111242
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0040882{col 30}{space 2} .0007926{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0056418{col 71}{space 3}-.0025347
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0201527{col 30}{space 2} .0085621{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0033714{col 71}{space 3}  .036934
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0009293{col 30}{space 2} .0001571{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0006215{col 71}{space 3} .0012372
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .050078{col 30}{space 2} .0059027{col 41}{space 1}    8.48{col 50}{space 3}0.000{col 58}{space 4} .0385088{col 71}{space 3} .0616471
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0424076{col 30}{space 2} .0050708{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .0324691{col 71}{space 3} .0523461
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0066102{col 30}{space 2} .0065437{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.0062153{col 71}{space 3} .0194357
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0363254{col 30}{space 2} .0070309{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .0225451{col 71}{space 3} .0501056
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0143347{col 30}{space 2} .0074933{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4} -.000352{col 71}{space 3} .0290213
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0335737{col 30}{space 2} .0075956{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .0186866{col 71}{space 3} .0484607
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0479779{col 30}{space 2}  .006673{col 41}{space 1}    7.19{col 50}{space 3}0.000{col 58}{space 4}  .034899{col 71}{space 3} .0610568
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0034832{col 30}{space 2} .0085787{col 41}{space 1}   -0.41{col 50}{space 3}0.685{col 58}{space 4}-.0202971{col 71}{space 3} .0133307
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0020825{col 30}{space 2}  .001467{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4}-.0049578{col 71}{space 3} .0007928
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0675272{col 30}{space 2} .0100063{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .0479153{col 71}{space 3} .0871392
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0006477{col 30}{space 2}  .008949{col 41}{space 1}    0.07{col 50}{space 3}0.942{col 58}{space 4}-.0168921{col 71}{space 3} .0181874
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .156139{col 30}{space 2} .0107254{col 41}{space 1}   14.56{col 50}{space 3}0.000{col 58}{space 4} .1351176{col 71}{space 3} .1771604
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1277019{col 30}{space 2} .0097187{col 41}{space 1}   13.14{col 50}{space 3}0.000{col 58}{space 4} .1086536{col 71}{space 3} .1467502
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}   .03339{col 30}{space 2} .0100459{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0137005{col 71}{space 3} .0530796
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0089463{col 30}{space 2} .0087003{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.0259987{col 71}{space 3}  .008106
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0118948{col 30}{space 2} .0018339{col 41}{space 1}   -6.49{col 50}{space 3}0.000{col 58}{space 4}-.0154892{col 71}{space 3}-.0083005
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0963379{col 30}{space 2} .0051408{col 41}{space 1}  -18.74{col 50}{space 3}0.000{col 58}{space 4}-.1064137{col 71}{space 3}-.0862621
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0793926{col 30}{space 2} .0051742{col 41}{space 1}  -15.34{col 50}{space 3}0.000{col 58}{space 4}-.0895339{col 71}{space 3}-.0692513
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} -.054105{col 30}{space 2} .0050058{col 41}{space 1}  -10.81{col 50}{space 3}0.000{col 58}{space 4}-.0639162{col 71}{space 3}-.0442938
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.523053{col 30}{space 2} .0133971{col 41}{space 1}  113.69{col 50}{space 3}0.000{col 58}{space 4} 1.496796{col 71}{space 3} 1.549311
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    18,592
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0495455{col 30}{space 2} .0086512{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} .0325895{col 71}{space 3} .0665014
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0244419{col 30}{space 2} .0047402{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0337326{col 71}{space 3}-.0151512
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1204847{col 30}{space 2}  .051192{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .0201502{col 71}{space 3} .2208192
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0055562{col 30}{space 2} .0009388{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0037161{col 71}{space 3} .0073963
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .2993957{col 30}{space 2}  .035244{col 41}{space 1}    8.49{col 50}{space 3}0.000{col 58}{space 4} .2303188{col 71}{space 3} .3684727
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2535376{col 30}{space 2} .0303241{col 41}{space 1}    8.36{col 50}{space 3}0.000{col 58}{space 4} .1941036{col 71}{space 3} .3129717
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0395196{col 30}{space 2} .0391216{col 41}{space 1}    1.01{col 50}{space 3}0.312{col 58}{space 4}-.0371574{col 71}{space 3} .1161965
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2171746{col 30}{space 2} .0420336{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .1347902{col 71}{space 3}  .299559
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0857013{col 30}{space 2} .0448011{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0021073{col 71}{space 3} .1735098
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2007232{col 30}{space 2} .0454036{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1117338{col 71}{space 3} .2897126
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2868403{col 30}{space 2} .0398899{col 41}{space 1}    7.19{col 50}{space 3}0.000{col 58}{space 4} .2086575{col 71}{space 3}  .365023
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0208248{col 30}{space 2} .0512892{col 41}{space 1}   -0.41{col 50}{space 3}0.685{col 58}{space 4}-.1213498{col 71}{space 3} .0797002
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0124504{col 30}{space 2} .0087705{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4}-.0296402{col 71}{space 3} .0047394
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .4037179{col 30}{space 2} .0598187{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .2864754{col 71}{space 3} .5209604
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0038722{col 30}{space 2} .0535027{col 41}{space 1}    0.07{col 50}{space 3}0.942{col 58}{space 4}-.1009911{col 71}{space 3} .1087356
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9334916{col 30}{space 2}  .064045{col 41}{space 1}   14.58{col 50}{space 3}0.000{col 58}{space 4} .8079658{col 71}{space 3} 1.059017
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7634775{col 30}{space 2} .0581031{col 41}{space 1}   13.14{col 50}{space 3}0.000{col 58}{space 4} .6495974{col 71}{space 3} .8773576
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1996255{col 30}{space 2} .0600553{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0819192{col 71}{space 3} .3173317
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0534864{col 30}{space 2} .0520182{col 41}{space 1}   -1.03{col 50}{space 3}0.304{col 58}{space 4}-.1554402{col 71}{space 3} .0484674
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0711144{col 30}{space 2} .0109644{col 41}{space 1}   -6.49{col 50}{space 3}0.000{col 58}{space 4}-.0926043{col 71}{space 3}-.0496245
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5759649{col 30}{space 2} .0305816{col 41}{space 1}  -18.83{col 50}{space 3}0.000{col 58}{space 4}-.6359038{col 71}{space 3} -.516026
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4746559{col 30}{space 2} .0307832{col 41}{space 1}  -15.42{col 50}{space 3}0.000{col 58}{space 4}-.5349898{col 71}{space 3} -.414322
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3234718{col 30}{space 2} .0298426{col 41}{space 1}  -10.84{col 50}{space 3}0.000{col 58}{space 4}-.3819622{col 71}{space 3}-.2649815
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  no_species   $xlist  no_species_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-42171.955}  
Iteration 1:{space 3}log pseudolikelihood = {res:-42171.955}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    21,117
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   3767.29
{txt}Log pseudolikelihood = {res}-42171.955{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0096967{col 30}{space 2} .0009666{col 41}{space 1}   10.03{col 50}{space 3}0.000{col 58}{space 4} .0078021{col 71}{space 3} .0115913
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0014879{col 30}{space 2} .0007678{col 41}{space 1}   -1.94{col 50}{space 3}0.053{col 58}{space 4}-.0029927{col 71}{space 3} .0000169
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0082662{col 30}{space 2} .0090866{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0095433{col 71}{space 3} .0260756
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000092{col 30}{space 2} .0001458{col 41}{space 1}   -0.63{col 50}{space 3}0.528{col 58}{space 4}-.0003777{col 71}{space 3} .0001937
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0140659{col 30}{space 2} .0048038{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0046507{col 71}{space 3} .0234811
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0624914{col 30}{space 2} .0053763{col 41}{space 1}   11.62{col 50}{space 3}0.000{col 58}{space 4} .0519539{col 71}{space 3} .0730288
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0276138{col 30}{space 2} .0090839{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .0098097{col 71}{space 3}  .045418
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0594973{col 30}{space 2} .0071852{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4} .0454146{col 71}{space 3}   .07358
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0115985{col 30}{space 2} .0070753{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4}-.0022687{col 71}{space 3} .0254658
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0253538{col 30}{space 2} .0051569{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0152465{col 71}{space 3} .0354612
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0454859{col 30}{space 2} .0054094{col 41}{space 1}    8.41{col 50}{space 3}0.000{col 58}{space 4} .0348836{col 71}{space 3} .0560882
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0327495{col 30}{space 2} .0047936{col 41}{space 1}   -6.83{col 50}{space 3}0.000{col 58}{space 4}-.0421447{col 71}{space 3}-.0233543
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0000243{col 30}{space 2} .0004078{col 41}{space 1}    0.06{col 50}{space 3}0.953{col 58}{space 4} -.000775{col 71}{space 3} .0008235
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  -.00531{col 30}{space 2}   .00552{col 41}{space 1}   -0.96{col 50}{space 3}0.336{col 58}{space 4}-.0161289{col 71}{space 3} .0055089
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0693589{col 30}{space 2} .0115791{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .0466642{col 71}{space 3} .0920536
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0808386{col 30}{space 2} .0097858{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4} .0616587{col 71}{space 3} .1000185
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0944505{col 30}{space 2} .0090006{col 41}{space 1}   10.49{col 50}{space 3}0.000{col 58}{space 4} .0768097{col 71}{space 3} .1120912
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .015322{col 30}{space 2} .0072355{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0011407{col 71}{space 3} .0295033
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .036449{col 30}{space 2} .0073925{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4}   .02196{col 71}{space 3} .0509381
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0045028{col 30}{space 2} .0011295{col 41}{space 1}   -3.99{col 50}{space 3}0.000{col 58}{space 4}-.0067166{col 71}{space 3}-.0022889
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0334552{col 30}{space 2}  .005134{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .0233926{col 71}{space 3} .0435177
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  .027408{col 30}{space 2} .0042529{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .0190724{col 71}{space 3} .0357436
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0131442{col 30}{space 2} .0045994{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0041296{col 71}{space 3} .0221587
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.490627{col 30}{space 2} .0111285{col 41}{space 1}  133.95{col 50}{space 3}0.000{col 58}{space 4} 1.468815{col 71}{space 3} 1.512438
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    21,117
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0573403{col 30}{space 2} .0057082{col 41}{space 1}   10.05{col 50}{space 3}0.000{col 58}{space 4} .0461525{col 71}{space 3} .0685281
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0087986{col 30}{space 2} .0045413{col 41}{space 1}   -1.94{col 50}{space 3}0.053{col 58}{space 4}-.0176993{col 71}{space 3} .0001021
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .048881{col 30}{space 2} .0537301{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0564279{col 71}{space 3}   .15419
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000544{col 30}{space 2} .0008619{col 41}{space 1}   -0.63{col 50}{space 3}0.528{col 58}{space 4}-.0022332{col 71}{space 3} .0011453
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0831773{col 30}{space 2}  .028406{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0275025{col 71}{space 3} .1388521
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3695357{col 30}{space 2} .0318038{col 41}{space 1}   11.62{col 50}{space 3}0.000{col 58}{space 4} .3072014{col 71}{space 3} .4318701
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1632914{col 30}{space 2} .0537167{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .0580086{col 71}{space 3} .2685741
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3518307{col 30}{space 2}  .042489{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4} .2685537{col 71}{space 3} .4351076
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0685865{col 30}{space 2} .0418376{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4}-.0134137{col 71}{space 3} .1505868
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .149927{col 30}{space 2} .0304931{col 41}{space 1}    4.92{col 50}{space 3}0.000{col 58}{space 4} .0901617{col 71}{space 3} .2096923
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2689758{col 30}{space 2} .0319861{col 41}{space 1}    8.41{col 50}{space 3}0.000{col 58}{space 4} .2062842{col 71}{space 3} .3316673
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1936604{col 30}{space 2} .0283393{col 41}{space 1}   -6.83{col 50}{space 3}0.000{col 58}{space 4}-.2492045{col 71}{space 3}-.1381164
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0001436{col 30}{space 2} .0024114{col 41}{space 1}    0.06{col 50}{space 3}0.953{col 58}{space 4}-.0045827{col 71}{space 3} .0048699
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0314001{col 30}{space 2} .0326405{col 41}{space 1}   -0.96{col 50}{space 3}0.336{col 58}{space 4}-.0953742{col 71}{space 3} .0325741
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4101459{col 30}{space 2} .0684675{col 41}{space 1}    5.99{col 50}{space 3}0.000{col 58}{space 4} .2759521{col 71}{space 3} .5443397
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .47803{col 30}{space 2} .0578643{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4}  .364618{col 71}{space 3}  .591442
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5585221{col 30}{space 2} .0531877{col 41}{space 1}   10.50{col 50}{space 3}0.000{col 58}{space 4} .4542761{col 71}{space 3} .6627681
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0906049{col 30}{space 2} .0427882{col 41}{space 1}    2.12{col 50}{space 3}0.034{col 58}{space 4} .0067415{col 71}{space 3} .1744683
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2155371{col 30}{space 2} .0437101{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .1298669{col 71}{space 3} .3012074
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0266265{col 30}{space 2} .0066764{col 41}{space 1}   -3.99{col 50}{space 3}0.000{col 58}{space 4} -.039712{col 71}{space 3}-.0135411
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .1978333{col 30}{space 2} .0303807{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .1382882{col 71}{space 3} .2573783
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .1620739{col 30}{space 2} .0251512{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .1127785{col 71}{space 3} .2113693
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0777265{col 30}{space 2} .0271894{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0244362{col 71}{space 3} .1310169
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. poisson hdd9  no_species   $xlist  no_species_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-40495.999}  
Iteration 1:{space 3}log pseudolikelihood = {res:-40495.999}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    20,313
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   2881.60
{txt}Log pseudolikelihood = {res}-40495.999{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0087878{col 30}{space 2} .0009735{col 41}{space 1}    9.03{col 50}{space 3}0.000{col 58}{space 4} .0068798{col 71}{space 3} .0106957
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .002085{col 30}{space 2} .0009251{col 41}{space 1}    2.25{col 50}{space 3}0.024{col 58}{space 4} .0002718{col 71}{space 3} .0038983
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .026972{col 30}{space 2} .0107104{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0059799{col 71}{space 3} .0479641
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003918{col 30}{space 2} .0001781{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.0007409{col 71}{space 3}-.0000428
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0138749{col 30}{space 2} .0058145{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4} .0024788{col 71}{space 3}  .025271
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0662808{col 30}{space 2} .0060704{col 41}{space 1}   10.92{col 50}{space 3}0.000{col 58}{space 4} .0543831{col 71}{space 3} .0781786
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .033644{col 30}{space 2} .0080347{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .0178962{col 71}{space 3} .0493918
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0478167{col 30}{space 2}   .00634{col 41}{space 1}    7.54{col 50}{space 3}0.000{col 58}{space 4} .0353906{col 71}{space 3} .0602428
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0581975{col 30}{space 2} .0057932{col 41}{space 1}   10.05{col 50}{space 3}0.000{col 58}{space 4} .0468431{col 71}{space 3} .0695519
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0103385{col 30}{space 2} .0048986{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0007374{col 71}{space 3} .0199396
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0339111{col 30}{space 2} .0049956{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .0241199{col 71}{space 3} .0437022
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0158731{col 30}{space 2} .0046952{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4}-.0250756{col 71}{space 3}-.0066706
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003204{col 30}{space 2} .0002445{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0001589{col 71}{space 3} .0007997
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0128407{col 30}{space 2} .0054717{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.0235649{col 71}{space 3}-.0021164
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0283394{col 30}{space 2} .0125452{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0037513{col 71}{space 3} .0529274
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0700008{col 30}{space 2} .0111029{col 41}{space 1}    6.30{col 50}{space 3}0.000{col 58}{space 4} .0482396{col 71}{space 3}  .091762
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0789978{col 30}{space 2} .0106508{col 41}{space 1}    7.42{col 50}{space 3}0.000{col 58}{space 4} .0581227{col 71}{space 3}  .099873
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0258765{col 30}{space 2} .0092793{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0076894{col 71}{space 3} .0440635
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0591989{col 30}{space 2} .0089109{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .0417339{col 71}{space 3} .0766639
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0000866{col 30}{space 2} .0013376{col 41}{space 1}   -0.06{col 50}{space 3}0.948{col 58}{space 4}-.0027083{col 71}{space 3}  .002535
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0372242{col 30}{space 2} .0062205{col 41}{space 1}   -5.98{col 50}{space 3}0.000{col 58}{space 4}-.0494162{col 71}{space 3}-.0250323
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} -.013831{col 30}{space 2} .0057172{col 41}{space 1}   -2.42{col 50}{space 3}0.016{col 58}{space 4}-.0250366{col 71}{space 3}-.0026254
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0602126{col 30}{space 2} .0054395{col 41}{space 1}   11.07{col 50}{space 3}0.000{col 58}{space 4} .0495513{col 71}{space 3} .0708739
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0155273{col 30}{space 2} .0055175{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0047131{col 71}{space 3} .0263414
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0511427{col 30}{space 2} .0051816{col 41}{space 1}    9.87{col 50}{space 3}0.000{col 58}{space 4}  .040987{col 71}{space 3} .0612984
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  1.43676{col 30}{space 2} .0147444{col 41}{space 1}   97.44{col 50}{space 3}0.000{col 58}{space 4} 1.407862{col 71}{space 3} 1.465659
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    20,313
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:no_species hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean no_species_mean year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}no_species {c |}{col 18}{res}{space 2} .0497861{col 30}{space 2} .0055125{col 41}{space 1}    9.03{col 50}{space 3}0.000{col 58}{space 4} .0389819{col 71}{space 3} .0605904
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0118126{col 30}{space 2} .0052412{col 41}{space 1}    2.25{col 50}{space 3}0.024{col 58}{space 4} .0015401{col 71}{space 3}  .022085
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1528067{col 30}{space 2} .0606654{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0339047{col 71}{space 3} .2717087
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022199{col 30}{space 2}  .001009{col 41}{space 1}   -2.20{col 50}{space 3}0.028{col 58}{space 4}-.0041974{col 71}{space 3}-.0002424
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0786067{col 30}{space 2} .0329346{col 41}{space 1}    2.39{col 50}{space 3}0.017{col 58}{space 4}  .014056{col 71}{space 3} .1431574
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3755066{col 30}{space 2} .0343659{col 41}{space 1}   10.93{col 50}{space 3}0.000{col 58}{space 4} .3081506{col 71}{space 3} .4428626
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1906063{col 30}{space 2} .0455105{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1014074{col 71}{space 3} .2798051
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2709002{col 30}{space 2} .0358999{col 41}{space 1}    7.55{col 50}{space 3}0.000{col 58}{space 4} .2005378{col 71}{space 3} .3412626
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3297115{col 30}{space 2} .0328122{col 41}{space 1}   10.05{col 50}{space 3}0.000{col 58}{space 4} .2654007{col 71}{space 3} .3940223
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0585716{col 30}{space 2} .0277577{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .0041676{col 71}{space 3} .1129757
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1921195{col 30}{space 2} .0283108{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .1366313{col 71}{space 3} .2476077
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0899271{col 30}{space 2} .0266025{col 41}{space 1}   -3.38{col 50}{space 3}0.001{col 58}{space 4} -.142067{col 71}{space 3}-.0377873
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0018152{col 30}{space 2} .0013855{col 41}{space 1}    1.31{col 50}{space 3}0.190{col 58}{space 4}-.0009003{col 71}{space 3} .0045308
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0727475{col 30}{space 2} .0309966{col 41}{space 1}   -2.35{col 50}{space 3}0.019{col 58}{space 4}-.1334997{col 71}{space 3}-.0119952
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1605534{col 30}{space 2} .0710685{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0212618{col 71}{space 3} .2998451
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3965817{col 30}{space 2} .0628371{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .2734233{col 71}{space 3} .5197401
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4475532{col 30}{space 2} .0603076{col 41}{space 1}    7.42{col 50}{space 3}0.000{col 58}{space 4} .3293526{col 71}{space 3} .5657539
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1466002{col 30}{space 2} .0525874{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0435307{col 71}{space 3} .2496696
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3353846{col 30}{space 2} .0504901{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .2364258{col 71}{space 3} .4343433
{txt}{space 1}no_species_mean {c |}{col 18}{res}{space 2}-.0004909{col 30}{space 2} .0075782{col 41}{space 1}   -0.06{col 50}{space 3}0.948{col 58}{space 4}-.0153439{col 71}{space 3} .0143621
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2108897{col 30}{space 2}  .035204{col 41}{space 1}   -5.99{col 50}{space 3}0.000{col 58}{space 4}-.2798883{col 71}{space 3}-.1418912
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0783578{col 30}{space 2} .0323917{col 41}{space 1}   -2.42{col 50}{space 3}0.016{col 58}{space 4}-.1418444{col 71}{space 3}-.0148712
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3411277{col 30}{space 2} .0307878{col 41}{space 1}   11.08{col 50}{space 3}0.000{col 58}{space 4} .2807848{col 71}{space 3} .4014705
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0879679{col 30}{space 2} .0312537{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0267117{col 71}{space 3} .1492241
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2897432{col 30}{space 2} .0293614{col 41}{space 1}    9.87{col 50}{space 3}0.000{col 58}{space 4} .2321958{col 71}{space 3} .3472905
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. 
. esttab using  S20_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(no_species   $xlist  no_species_mean)  
{res}{txt}(note: file S20_poisson.rtf not found)
(output written to {browse  `"S20_poisson.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                                   S21                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. 
. poisson hdd9  pdd9   $xlist   pdd9_mean i.country i.year, cluster(HHID_panel)
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-177948.62}  
Iteration 1:{space 3}log pseudolikelihood = {res:-177948.61}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 49}Wald chi2({res}35{txt}){col 67}= {res}  24731.29
{txt}Log pseudolikelihood = {res}-177948.61{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:36,644} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0182259{col 30}{space 2} .0009422{col 41}{space 1}   19.34{col 50}{space 3}0.000{col 58}{space 4} .0163792{col 71}{space 3} .0200727
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0012381{col 30}{space 2}  .000404{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.0020299{col 71}{space 3}-.0004463
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0086671{col 30}{space 2} .0045512{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0002531{col 71}{space 3} .0175874
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000047{col 30}{space 2} .0000761{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4} -.000102{col 71}{space 3} .0001961
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0137368{col 30}{space 2} .0026555{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .0085322{col 71}{space 3} .0189414
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0668167{col 30}{space 2} .0026028{col 41}{space 1}   25.67{col 50}{space 3}0.000{col 58}{space 4} .0617153{col 71}{space 3} .0719181
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0194649{col 30}{space 2} .0041325{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .0113654{col 71}{space 3} .0275643
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0424052{col 30}{space 2} .0032516{col 41}{space 1}   13.04{col 50}{space 3}0.000{col 58}{space 4} .0360322{col 71}{space 3} .0487782
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0318711{col 30}{space 2} .0034316{col 41}{space 1}    9.29{col 50}{space 3}0.000{col 58}{space 4} .0251454{col 71}{space 3} .0385968
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0222678{col 30}{space 2} .0028716{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .0166395{col 71}{space 3} .0278961
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0387927{col 30}{space 2}  .002729{col 41}{space 1}   14.21{col 50}{space 3}0.000{col 58}{space 4}  .033444{col 71}{space 3} .0441415
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0281553{col 30}{space 2} .0024897{col 41}{space 1}  -11.31{col 50}{space 3}0.000{col 58}{space 4}-.0330351{col 71}{space 3}-.0232756
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0000545{col 30}{space 2} .0001901{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0004272{col 71}{space 3} .0003181
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0213759{col 30}{space 2} .0028948{col 41}{space 1}    7.38{col 50}{space 3}0.000{col 58}{space 4} .0157023{col 71}{space 3} .0270495
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .005474{col 30}{space 2} .0056073{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0055161{col 71}{space 3} .0164641
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1080007{col 30}{space 2} .0048086{col 41}{space 1}   22.46{col 50}{space 3}0.000{col 58}{space 4}  .098576{col 71}{space 3} .1174254
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1170502{col 30}{space 2} .0046879{col 41}{space 1}   24.97{col 50}{space 3}0.000{col 58}{space 4} .1078621{col 71}{space 3} .1262383
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0363892{col 30}{space 2} .0042187{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .0281208{col 71}{space 3} .0446577
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0338842{col 30}{space 2} .0039141{col 41}{space 1}    8.66{col 50}{space 3}0.000{col 58}{space 4} .0262127{col 71}{space 3} .0415556
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0081878{col 30}{space 2} .0012119{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4}-.0105631{col 71}{space 3}-.0058126
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.0767436{col 30}{space 2} .0052994{col 41}{space 1}  -14.48{col 50}{space 3}0.000{col 58}{space 4}-.0871303{col 71}{space 3}-.0663569
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.2860751{col 30}{space 2} .0056697{col 41}{space 1}  -50.46{col 50}{space 3}0.000{col 58}{space 4}-.2971874{col 71}{space 3}-.2749627
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.0831146{col 30}{space 2} .0052632{col 41}{space 1}  -15.79{col 50}{space 3}0.000{col 58}{space 4}-.0934303{col 71}{space 3}-.0727989
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.0506269{col 30}{space 2} .0049634{col 41}{space 1}  -10.20{col 50}{space 3}0.000{col 58}{space 4} -.060355{col 71}{space 3}-.0408987
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .0953799{col 30}{space 2} .0058423{col 41}{space 1}   16.33{col 50}{space 3}0.000{col 58}{space 4} .0839293{col 71}{space 3} .1068305
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0517172{col 30}{space 2} .0072108{col 41}{space 1}   -7.17{col 50}{space 3}0.000{col 58}{space 4}-.0658501{col 71}{space 3}-.0375843
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0179698{col 30}{space 2} .0049176{col 41}{space 1}   -3.65{col 50}{space 3}0.000{col 58}{space 4} -.027608{col 71}{space 3}-.0083315
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0169005{col 30}{space 2} .0058445{col 41}{space 1}   -2.89{col 50}{space 3}0.004{col 58}{space 4}-.0283555{col 71}{space 3}-.0054454
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0063264{col 30}{space 2} .0049592{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0160463{col 71}{space 3} .0033934
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}-.0037753{col 30}{space 2} .0056818{col 41}{space 1}   -0.66{col 50}{space 3}0.506{col 58}{space 4}-.0149114{col 71}{space 3} .0073609
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0355435{col 30}{space 2}   .00563{col 41}{space 1}   -6.31{col 50}{space 3}0.000{col 58}{space 4} -.046578{col 71}{space 3} -.024509
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .015238{col 30}{space 2} .0054489{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0045583{col 71}{space 3} .0259177
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0496626{col 30}{space 2} .0072511{col 41}{space 1}   -6.85{col 50}{space 3}0.000{col 58}{space 4}-.0638745{col 71}{space 3}-.0354508
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0529337{col 30}{space 2} .0057591{col 41}{space 1}    9.19{col 50}{space 3}0.000{col 58}{space 4} .0416461{col 71}{space 3} .0642214
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} -.039694{col 30}{space 2} .0052938{col 41}{space 1}   -7.50{col 50}{space 3}0.000{col 58}{space 4}-.0500696{col 71}{space 3}-.0293184
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.533196{col 30}{space 2} .0083741{col 41}{space 1}  183.09{col 50}{space 3}0.000{col 58}{space 4} 1.516783{col 71}{space 3} 1.549609
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    89,742
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1032256{col 30}{space 2} .0053329{col 41}{space 1}   19.36{col 50}{space 3}0.000{col 58}{space 4} .0927733{col 71}{space 3} .1136779
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0070122{col 30}{space 2} .0022881{col 41}{space 1}   -3.06{col 50}{space 3}0.002{col 58}{space 4}-.0114968{col 71}{space 3}-.0025276
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0490878{col 30}{space 2} .0257758{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0014319{col 71}{space 3} .0996075
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002663{col 30}{space 2} .0004307{col 41}{space 1}    0.62{col 50}{space 3}0.536{col 58}{space 4}-.0005779{col 71}{space 3} .0011105
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0778008{col 30}{space 2} .0150387{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .0483254{col 71}{space 3} .1072761
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3784277{col 30}{space 2} .0147416{col 41}{space 1}   25.67{col 50}{space 3}0.000{col 58}{space 4} .3495347{col 71}{space 3} .4073208
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1102426{col 30}{space 2} .0234042{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .0643711{col 71}{space 3}  .156114
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2401692{col 30}{space 2} .0184152{col 41}{space 1}   13.04{col 50}{space 3}0.000{col 58}{space 4} .2040761{col 71}{space 3} .2762623
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1805073{col 30}{space 2} .0194353{col 41}{space 1}    9.29{col 50}{space 3}0.000{col 58}{space 4} .1424148{col 71}{space 3} .2185998
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1261175{col 30}{space 2} .0162641{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .0942404{col 71}{space 3} .1579945
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2197093{col 30}{space 2} .0154559{col 41}{space 1}   14.22{col 50}{space 3}0.000{col 58}{space 4} .1894162{col 71}{space 3} .2500023
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1594624{col 30}{space 2} .0141007{col 41}{space 1}  -11.31{col 50}{space 3}0.000{col 58}{space 4}-.1870993{col 71}{space 3}-.1318254
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0003089{col 30}{space 2} .0010769{col 41}{space 1}   -0.29{col 50}{space 3}0.774{col 58}{space 4}-.0024195{col 71}{space 3} .0018017
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1210662{col 30}{space 2} .0163957{col 41}{space 1}    7.38{col 50}{space 3}0.000{col 58}{space 4} .0889313{col 71}{space 3} .1532011
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0310028{col 30}{space 2} .0317577{col 41}{space 1}    0.98{col 50}{space 3}0.329{col 58}{space 4}-.0312412{col 71}{space 3} .0932467
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6116801{col 30}{space 2} .0272121{col 41}{space 1}   22.48{col 50}{space 3}0.000{col 58}{space 4} .5583453{col 71}{space 3} .6650149
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6629337{col 30}{space 2}  .026526{col 41}{space 1}   24.99{col 50}{space 3}0.000{col 58}{space 4} .6109436{col 71}{space 3} .7149238
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2060966{col 30}{space 2}  .023894{col 41}{space 1}    8.63{col 50}{space 3}0.000{col 58}{space 4} .1592653{col 71}{space 3} .2529279
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1919087{col 30}{space 2} .0221659{col 41}{space 1}    8.66{col 50}{space 3}0.000{col 58}{space 4} .1484644{col 71}{space 3} .2353531
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0463733{col 30}{space 2} .0068641{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4}-.0598266{col 71}{space 3}-.0329199
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4512526{col 30}{space 2} .0316273{col 41}{space 1}  -14.27{col 50}{space 3}0.000{col 58}{space 4}-.5132409{col 71}{space 3}-.3892642
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.519761{col 30}{space 2}  .031232{col 41}{space 1}  -48.66{col 50}{space 3}0.000{col 58}{space 4}-1.580974{col 71}{space 3}-1.458547
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.4871805{col 30}{space 2} .0313756{col 41}{space 1}  -15.53{col 50}{space 3}0.000{col 58}{space 4}-.5486756{col 71}{space 3}-.4256855
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3015572{col 30}{space 2} .0299573{col 41}{space 1}  -10.07{col 50}{space 3}0.000{col 58}{space 4}-.3602724{col 71}{space 3}-.2428419
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6113201{col 30}{space 2} .0372107{col 41}{space 1}   16.43{col 50}{space 3}0.000{col 58}{space 4} .5383886{col 71}{space 3} .6842517
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2883832{col 30}{space 2} .0401121{col 41}{space 1}   -7.19{col 50}{space 3}0.000{col 58}{space 4}-.3670015{col 71}{space 3}-.2097649
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.1018974{col 30}{space 2} .0280629{col 41}{space 1}   -3.63{col 50}{space 3}0.000{col 58}{space 4}-.1568997{col 71}{space 3}-.0468951
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} -.095885{col 30}{space 2} .0332638{col 41}{space 1}   -2.88{col 50}{space 3}0.004{col 58}{space 4}-.1610809{col 71}{space 3}-.0306891
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0360831{col 30}{space 2} .0283398{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4}-.0916281{col 71}{space 3} .0194619
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}-.0215598{col 30}{space 2} .0324753{col 41}{space 1}   -0.66{col 50}{space 3}0.507{col 58}{space 4}-.0852102{col 71}{space 3} .0420906
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1997937{col 30}{space 2} .0318442{col 41}{space 1}   -6.27{col 50}{space 3}0.000{col 58}{space 4}-.2622071{col 71}{space 3}-.1373803
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0878533{col 30}{space 2} .0312827{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0265404{col 71}{space 3} .1491662
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2772088{col 30}{space 2} .0403675{col 41}{space 1}   -6.87{col 50}{space 3}0.000{col 58}{space 4}-.3563276{col 71}{space 3}-.1980901
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3110245{col 30}{space 2} .0335036{col 41}{space 1}    9.28{col 50}{space 3}0.000{col 58}{space 4} .2453587{col 71}{space 3} .3766903
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.2226645{col 30}{space 2} .0300293{col 41}{space 1}   -7.41{col 50}{space 3}0.000{col 58}{space 4}-.2815208{col 71}{space 3}-.1638083
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-25095.665}  
Iteration 1:{space 3}log pseudolikelihood = {res:-25095.665}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    13,511
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   3522.71
{txt}Log pseudolikelihood = {res}-25095.665{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,436} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0109502{col 30}{space 2} .0025249{col 41}{space 1}    4.34{col 50}{space 3}0.000{col 58}{space 4} .0060015{col 71}{space 3} .0158988
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0103935{col 30}{space 2} .0016226{col 41}{space 1}    6.41{col 50}{space 3}0.000{col 58}{space 4} .0072133{col 71}{space 3} .0135737
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0070072{col 30}{space 2}  .013201{col 41}{space 1}   -0.53{col 50}{space 3}0.596{col 58}{space 4}-.0328807{col 71}{space 3} .0188664
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0009165{col 30}{space 2} .0002244{col 41}{space 1}   -4.09{col 50}{space 3}0.000{col 58}{space 4}-.0013563{col 71}{space 3}-.0004768
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0042141{col 30}{space 2} .0076823{col 41}{space 1}    0.55{col 50}{space 3}0.583{col 58}{space 4}-.0108429{col 71}{space 3} .0192711
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1030335{col 30}{space 2} .0071638{col 41}{space 1}   14.38{col 50}{space 3}0.000{col 58}{space 4} .0889927{col 71}{space 3} .1170742
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0289446{col 30}{space 2} .0252405{col 41}{space 1}   -1.15{col 50}{space 3}0.251{col 58}{space 4} -.078415{col 71}{space 3} .0205258
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0438611{col 30}{space 2} .0085869{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4}  .027031{col 71}{space 3} .0606911
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0383804{col 30}{space 2} .0102422{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4}  .018306{col 71}{space 3} .0584547
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0067451{col 30}{space 2} .0107433{col 41}{space 1}   -0.63{col 50}{space 3}0.530{col 58}{space 4}-.0278016{col 71}{space 3} .0143115
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0468831{col 30}{space 2} .0104514{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .0263988{col 71}{space 3} .0673674
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0676105{col 30}{space 2} .0078589{col 41}{space 1}   -8.60{col 50}{space 3}0.000{col 58}{space 4}-.0830136{col 71}{space 3}-.0522075
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0010531{col 30}{space 2} .0008849{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0006814{col 71}{space 3} .0027875
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0640848{col 30}{space 2} .0077628{col 41}{space 1}    8.26{col 50}{space 3}0.000{col 58}{space 4}   .04887{col 71}{space 3} .0792995
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1967774{col 30}{space 2} .0387421{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .1208442{col 71}{space 3} .2727105
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1168566{col 30}{space 2} .0129295{col 41}{space 1}    9.04{col 50}{space 3}0.000{col 58}{space 4} .0915154{col 71}{space 3} .1421979
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1344431{col 30}{space 2} .0150863{col 41}{space 1}    8.91{col 50}{space 3}0.000{col 58}{space 4} .1048745{col 71}{space 3} .1640117
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1056509{col 30}{space 2} .0160976{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .0741002{col 71}{space 3} .1372016
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0184863{col 30}{space 2} .0131532{col 41}{space 1}    1.41{col 50}{space 3}0.160{col 58}{space 4}-.0072935{col 71}{space 3} .0442662
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0023683{col 30}{space 2} .0033409{col 41}{space 1}    0.71{col 50}{space 3}0.478{col 58}{space 4}-.0041798{col 71}{space 3} .0089163
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0405488{col 30}{space 2} .0048242{col 41}{space 1}   -8.41{col 50}{space 3}0.000{col 58}{space 4} -.050004{col 71}{space 3}-.0310935
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.198034{col 30}{space 2}  .015885{col 41}{space 1}   75.42{col 50}{space 3}0.000{col 58}{space 4}   1.1669{col 71}{space 3} 1.229168
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    13,511
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0484511{col 30}{space 2} .0111711{col 41}{space 1}    4.34{col 50}{space 3}0.000{col 58}{space 4}  .026556{col 71}{space 3} .0703461
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0459881{col 30}{space 2} .0071802{col 41}{space 1}    6.40{col 50}{space 3}0.000{col 58}{space 4} .0319151{col 71}{space 3} .0600611
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0310046{col 30}{space 2} .0584087{col 41}{space 1}   -0.53{col 50}{space 3}0.596{col 58}{space 4}-.1454835{col 71}{space 3} .0834744
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0040554{col 30}{space 2} .0009928{col 41}{space 1}   -4.08{col 50}{space 3}0.000{col 58}{space 4}-.0060014{col 71}{space 3}-.0021095
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0186461{col 30}{space 2} .0339917{col 41}{space 1}    0.55{col 50}{space 3}0.583{col 58}{space 4}-.0479765{col 71}{space 3} .0852686
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4558912{col 30}{space 2} .0317353{col 41}{space 1}   14.37{col 50}{space 3}0.000{col 58}{space 4} .3936912{col 71}{space 3} .5180913
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1280708{col 30}{space 2}  .111682{col 41}{space 1}   -1.15{col 50}{space 3}0.251{col 58}{space 4}-.3469636{col 71}{space 3} .0908219
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1940717{col 30}{space 2} .0379978{col 41}{space 1}    5.11{col 50}{space 3}0.000{col 58}{space 4} .1195973{col 71}{space 3}  .268546
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1698212{col 30}{space 2} .0453109{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0810134{col 71}{space 3}  .258629
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.029845{col 30}{space 2} .0475373{col 41}{space 1}   -0.63{col 50}{space 3}0.530{col 58}{space 4}-.1230164{col 71}{space 3} .0633265
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2074433{col 30}{space 2} .0462407{col 41}{space 1}    4.49{col 50}{space 3}0.000{col 58}{space 4} .1168131{col 71}{space 3} .2980734
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2991558{col 30}{space 2} .0347711{col 41}{space 1}   -8.60{col 50}{space 3}0.000{col 58}{space 4}-.3673058{col 71}{space 3}-.2310057
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0046595{col 30}{space 2} .0039153{col 41}{space 1}    1.19{col 50}{space 3}0.234{col 58}{space 4}-.0030144{col 71}{space 3} .0123334
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2835554{col 30}{space 2} .0343672{col 41}{space 1}    8.25{col 50}{space 3}0.000{col 58}{space 4} .2161969{col 71}{space 3} .3509139
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .870679{col 30}{space 2} .1714295{col 41}{space 1}    5.08{col 50}{space 3}0.000{col 58}{space 4} .5346834{col 71}{space 3} 1.206675
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5170545{col 30}{space 2} .0572464{col 41}{space 1}    9.03{col 50}{space 3}0.000{col 58}{space 4} .4048537{col 71}{space 3} .6292552
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5948691{col 30}{space 2} .0667913{col 41}{space 1}    8.91{col 50}{space 3}0.000{col 58}{space 4} .4639606{col 71}{space 3} .7257776
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4674727{col 30}{space 2} .0711785{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .3279653{col 71}{space 3}   .60698
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0817963{col 30}{space 2} .0581936{col 41}{space 1}    1.41{col 50}{space 3}0.160{col 58}{space 4}-.0322611{col 71}{space 3} .1958536
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0104788{col 30}{space 2} .0147825{col 41}{space 1}    0.71{col 50}{space 3}0.478{col 58}{space 4}-.0184945{col 71}{space 3}  .039452
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1794157{col 30}{space 2} .0213269{col 41}{space 1}   -8.41{col 50}{space 3}0.000{col 58}{space 4}-.2212156{col 71}{space 3}-.1376158
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-18450.452}  
Iteration 1:{space 3}log pseudolikelihood = {res:-18450.451}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     9,163
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   3254.84
{txt}Log pseudolikelihood = {res}-18450.451{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0190309{col 30}{space 2} .0023227{col 41}{space 1}    8.19{col 50}{space 3}0.000{col 58}{space 4} .0144786{col 71}{space 3} .0235833
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0027938{col 30}{space 2} .0015226{col 41}{space 1}   -1.83{col 50}{space 3}0.067{col 58}{space 4}-.0057781{col 71}{space 3} .0001905
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  -.05629{col 30}{space 2}  .012417{col 41}{space 1}   -4.53{col 50}{space 3}0.000{col 58}{space 4}-.0806269{col 71}{space 3} -.031953
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0005586{col 30}{space 2} .0002169{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-.0009837{col 71}{space 3}-.0001336
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0164265{col 30}{space 2} .0072574{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.0306508{col 71}{space 3}-.0022023
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0591724{col 30}{space 2} .0082061{col 41}{space 1}    7.21{col 50}{space 3}0.000{col 58}{space 4} .0430887{col 71}{space 3} .0752561
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0344713{col 30}{space 2} .0195236{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0037942{col 71}{space 3} .0727367
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0434424{col 30}{space 2} .0088687{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .0260601{col 71}{space 3} .0608246
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0634789{col 30}{space 2} .0120969{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .0397694{col 71}{space 3} .0871885
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0277359{col 30}{space 2} .0088294{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0104307{col 71}{space 3} .0450411
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0411771{col 30}{space 2} .0065536{col 41}{space 1}    6.28{col 50}{space 3}0.000{col 58}{space 4} .0283322{col 71}{space 3}  .054022
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0386524{col 30}{space 2} .0056087{col 41}{space 1}   -6.89{col 50}{space 3}0.000{col 58}{space 4}-.0496453{col 71}{space 3}-.0276595
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .003675{col 30}{space 2} .0041562{col 41}{space 1}    0.88{col 50}{space 3}0.377{col 58}{space 4} -.004471{col 71}{space 3}  .011821
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0002813{col 30}{space 2}  .008212{col 41}{space 1}    0.03{col 50}{space 3}0.973{col 58}{space 4}-.0158139{col 71}{space 3} .0163765
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0408311{col 30}{space 2} .0306057{col 41}{space 1}    1.33{col 50}{space 3}0.182{col 58}{space 4} -.019155{col 71}{space 3} .1008173
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0837523{col 30}{space 2} .0128358{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .0585946{col 71}{space 3} .1089099
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0942153{col 30}{space 2} .0156566{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4} .0635289{col 71}{space 3} .1249018
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0595607{col 30}{space 2} .0121784{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .0356914{col 71}{space 3}   .08343
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0581221{col 30}{space 2} .0107541{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .0370444{col 71}{space 3} .0791997
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0106538{col 30}{space 2} .0033196{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4}-.0171601{col 71}{space 3}-.0041474
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0173416{col 30}{space 2} .0068739{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0038689{col 71}{space 3} .0308142
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0137906{col 30}{space 2} .0056929{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0026327{col 71}{space 3} .0249485
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.665841{col 30}{space 2} .0150274{col 41}{space 1}  110.85{col 50}{space 3}0.000{col 58}{space 4} 1.636388{col 71}{space 3} 1.695294
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     9,163
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1187756{col 30}{space 2} .0144885{col 41}{space 1}    8.20{col 50}{space 3}0.000{col 58}{space 4} .0903787{col 71}{space 3} .1471724
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0174367{col 30}{space 2} .0094996{col 41}{space 1}   -1.84{col 50}{space 3}0.066{col 58}{space 4}-.0360556{col 71}{space 3} .0011823
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.3513162{col 30}{space 2} .0775456{col 41}{space 1}   -4.53{col 50}{space 3}0.000{col 58}{space 4}-.5033028{col 71}{space 3}-.1993297
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0034865{col 30}{space 2}  .001353{col 41}{space 1}   -2.58{col 50}{space 3}0.010{col 58}{space 4}-.0061382{col 71}{space 3}-.0008347
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1025209{col 30}{space 2} .0452784{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4} -.191265{col 71}{space 3}-.0137768
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3693061{col 30}{space 2} .0511781{col 41}{space 1}    7.22{col 50}{space 3}0.000{col 58}{space 4} .2689989{col 71}{space 3} .4696133
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2151416{col 30}{space 2} .1218515{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0236828{col 71}{space 3} .4539661
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2711319{col 30}{space 2} .0553491{col 41}{space 1}    4.90{col 50}{space 3}0.000{col 58}{space 4} .1626496{col 71}{space 3} .3796141
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3961839{col 30}{space 2} .0754629{col 41}{space 1}    5.25{col 50}{space 3}0.000{col 58}{space 4} .2482793{col 71}{space 3} .5440885
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1731048{col 30}{space 2} .0551093{col 41}{space 1}    3.14{col 50}{space 3}0.002{col 58}{space 4} .0650925{col 71}{space 3} .2811171
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2569942{col 30}{space 2}  .040876{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4} .1768788{col 71}{space 3} .3371097
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2412367{col 30}{space 2} .0349986{col 41}{space 1}   -6.89{col 50}{space 3}0.000{col 58}{space 4}-.3098328{col 71}{space 3}-.1726407
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0229362{col 30}{space 2} .0259421{col 41}{space 1}    0.88{col 50}{space 3}0.377{col 58}{space 4}-.0279094{col 71}{space 3} .0737817
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0017559{col 30}{space 2} .0512525{col 41}{space 1}    0.03{col 50}{space 3}0.973{col 58}{space 4}-.0986972{col 71}{space 3}  .102209
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2548348{col 30}{space 2} .1909955{col 41}{space 1}    1.33{col 50}{space 3}0.182{col 58}{space 4}-.1195095{col 71}{space 3} .6291792
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5227138{col 30}{space 2} .0801292{col 41}{space 1}    6.52{col 50}{space 3}0.000{col 58}{space 4} .3656634{col 71}{space 3} .6797641
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5880156{col 30}{space 2} .0976262{col 41}{space 1}    6.02{col 50}{space 3}0.000{col 58}{space 4} .3966718{col 71}{space 3} .7793593
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3717295{col 30}{space 2} .0759626{col 41}{space 1}    4.89{col 50}{space 3}0.000{col 58}{space 4} .2228455{col 71}{space 3} .5206136
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3627508{col 30}{space 2} .0671173{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .2312032{col 71}{space 3} .4942983
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0664921{col 30}{space 2} .0207263{col 41}{space 1}   -3.21{col 50}{space 3}0.001{col 58}{space 4} -.107115{col 71}{space 3}-.0258693
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  .108232{col 30}{space 2}  .042895{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} .0241595{col 71}{space 3} .1923046
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0860694{col 30}{space 2} .0355329{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0164261{col 71}{space 3} .1557127
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-14087.762}  
Iteration 1:{space 3}log pseudolikelihood = {res:-14087.762}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     7,046
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   1621.33
{txt}Log pseudolikelihood = {res}-14087.762{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0437654{col 30}{space 2} .0062229{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .0315688{col 71}{space 3}  .055962
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0027312{col 30}{space 2} .0011051{col 41}{space 1}    2.47{col 50}{space 3}0.013{col 58}{space 4} .0005651{col 71}{space 3} .0048972
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0082056{col 30}{space 2} .0170675{col 41}{space 1}   -0.48{col 50}{space 3}0.631{col 58}{space 4}-.0416573{col 71}{space 3} .0252462
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004878{col 30}{space 2} .0002517{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-5.57e-06{col 71}{space 3} .0009811
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0179139{col 30}{space 2} .0101609{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0020011{col 71}{space 3} .0378289
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0614291{col 30}{space 2} .0075734{col 41}{space 1}    8.11{col 50}{space 3}0.000{col 58}{space 4} .0465855{col 71}{space 3} .0762727
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .039053{col 30}{space 2} .0155318{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0086112{col 71}{space 3} .0694948
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0170387{col 30}{space 2} .0136292{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.0096741{col 71}{space 3} .0437514
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0397492{col 30}{space 2} .0173043{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0058333{col 71}{space 3}  .073665
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0376015{col 30}{space 2} .0142148{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4}  .009741{col 71}{space 3} .0654619
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} -.031271{col 30}{space 2} .0118458{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.0544883{col 71}{space 3}-.0080537
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0282954{col 30}{space 2} .0085479{col 41}{space 1}   -3.31{col 50}{space 3}0.001{col 58}{space 4} -.045049{col 71}{space 3}-.0115418
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0003874{col 30}{space 2}  .000301{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.0009774{col 71}{space 3} .0002025
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .036205{col 30}{space 2} .0371935{col 41}{space 1}    0.97{col 50}{space 3}0.330{col 58}{space 4}-.0366929{col 71}{space 3} .1091029
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0154545{col 30}{space 2} .0191458{col 41}{space 1}    0.81{col 50}{space 3}0.420{col 58}{space 4}-.0220706{col 71}{space 3} .0529797
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0649329{col 30}{space 2} .0168106{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4} .0319848{col 71}{space 3}  .097881
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0773158{col 30}{space 2} .0202711{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .0375852{col 71}{space 3} .1170465
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0288248{col 30}{space 2}  .017565{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4} -.005602{col 71}{space 3} .0632517
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0806659{col 30}{space 2} .0145767{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .0520961{col 71}{space 3} .1092358
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0480223{col 30}{space 2} .0071095{col 41}{space 1}   -6.75{col 50}{space 3}0.000{col 58}{space 4}-.0619566{col 71}{space 3}-.0340879
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0442959{col 30}{space 2} .0064412{col 41}{space 1}    6.88{col 50}{space 3}0.000{col 58}{space 4} .0316713{col 71}{space 3} .0569205
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.533767{col 30}{space 2} .0198201{col 41}{space 1}   77.38{col 50}{space 3}0.000{col 58}{space 4}  1.49492{col 71}{space 3} 1.572614
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     7,046
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2496417{col 30}{space 2} .0354543{col 41}{space 1}    7.04{col 50}{space 3}0.000{col 58}{space 4} .1801525{col 71}{space 3}  .319131
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0155789{col 30}{space 2} .0063024{col 41}{space 1}    2.47{col 50}{space 3}0.013{col 58}{space 4} .0032264{col 71}{space 3} .0279313
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0468052{col 30}{space 2} .0973617{col 41}{space 1}   -0.48{col 50}{space 3}0.631{col 58}{space 4}-.2376306{col 71}{space 3} .1440201
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0027822{col 30}{space 2} .0014356{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0000315{col 71}{space 3} .0055959
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .1021827{col 30}{space 2} .0579585{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0114138{col 71}{space 3} .2157791
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .350397{col 30}{space 2} .0431573{col 41}{space 1}    8.12{col 50}{space 3}0.000{col 58}{space 4} .2658103{col 71}{space 3} .4349837
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2227618{col 30}{space 2} .0885741{col 41}{space 1}    2.51{col 50}{space 3}0.012{col 58}{space 4} .0491597{col 71}{space 3} .3963638
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0971901{col 30}{space 2}  .077736{col 41}{space 1}    1.25{col 50}{space 3}0.211{col 58}{space 4}-.0551697{col 71}{space 3} .2495499
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2267327{col 30}{space 2} .0986942{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0332956{col 71}{space 3} .4201698
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2144821{col 30}{space 2} .0810823{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0555638{col 71}{space 3} .3734005
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1783726{col 30}{space 2} .0675471{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.3107625{col 71}{space 3}-.0459827
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1613995{col 30}{space 2} .0487656{col 41}{space 1}   -3.31{col 50}{space 3}0.001{col 58}{space 4}-.2569783{col 71}{space 3}-.0658207
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  -.00221{col 30}{space 2} .0017171{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-.0055754{col 71}{space 3} .0011554
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2065165{col 30}{space 2} .2121523{col 41}{space 1}    0.97{col 50}{space 3}0.330{col 58}{space 4}-.2092943{col 71}{space 3} .6223273
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0881541{col 30}{space 2} .1092109{col 41}{space 1}    0.81{col 50}{space 3}0.420{col 58}{space 4}-.1258953{col 71}{space 3} .3022035
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3703829{col 30}{space 2} .0958723{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4} .1824767{col 71}{space 3} .5582891
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4410162{col 30}{space 2} .1156099{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .2144249{col 71}{space 3} .6676075
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1644194{col 30}{space 2}  .100178{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4}-.0319258{col 71}{space 3} .3607646
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4601254{col 30}{space 2} .0830498{col 41}{space 1}    5.54{col 50}{space 3}0.000{col 58}{space 4} .2973508{col 71}{space 3} .6229001
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2739231{col 30}{space 2}  .040519{col 41}{space 1}   -6.76{col 50}{space 3}0.000{col 58}{space 4}-.3533389{col 71}{space 3}-.1945074
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2526678{col 30}{space 2} .0366339{col 41}{space 1}    6.90{col 50}{space 3}0.000{col 58}{space 4} .1808667{col 71}{space 3} .3244688
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37270.202}  
Iteration 1:{space 3}log pseudolikelihood = {res:-37270.202}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    18,592
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   4646.63
{txt}Log pseudolikelihood = {res}-37270.202{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,222} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0165997{col 30}{space 2}  .002445{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .0118077{col 71}{space 3} .0213918
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0049561{col 30}{space 2} .0007872{col 41}{space 1}   -6.30{col 50}{space 3}0.000{col 58}{space 4} -.006499{col 71}{space 3}-.0034131
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .020967{col 30}{space 2} .0085571{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0041954{col 71}{space 3} .0377386
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000848{col 30}{space 2} .0001575{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0005394{col 71}{space 3} .0011566
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0517926{col 30}{space 2} .0058661{col 41}{space 1}    8.83{col 50}{space 3}0.000{col 58}{space 4} .0402953{col 71}{space 3} .0632898
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0433638{col 30}{space 2}  .005068{col 41}{space 1}    8.56{col 50}{space 3}0.000{col 58}{space 4} .0334307{col 71}{space 3} .0532969
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0071657{col 30}{space 2} .0065385{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0056495{col 71}{space 3} .0199809
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0364253{col 30}{space 2} .0070414{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .0226243{col 71}{space 3} .0502262
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0141775{col 30}{space 2} .0075066{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0005352{col 71}{space 3} .0288902
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0341582{col 30}{space 2} .0075921{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0192781{col 71}{space 3} .0490384
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0483018{col 30}{space 2} .0066562{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .0352559{col 71}{space 3} .0613478
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0070516{col 30}{space 2} .0085931{col 41}{space 1}   -0.82{col 50}{space 3}0.412{col 58}{space 4}-.0238938{col 71}{space 3} .0097906
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0028614{col 30}{space 2} .0018003{col 41}{space 1}   -1.59{col 50}{space 3}0.112{col 58}{space 4}-.0063899{col 71}{space 3}  .000667
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}   .06343{col 30}{space 2} .0098842{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4} .0440573{col 71}{space 3} .0828027
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0076022{col 30}{space 2} .0089855{col 41}{space 1}   -0.85{col 50}{space 3}0.398{col 58}{space 4}-.0252133{col 71}{space 3}  .010009
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1595404{col 30}{space 2} .0107073{col 41}{space 1}   14.90{col 50}{space 3}0.000{col 58}{space 4} .1385545{col 71}{space 3} .1805263
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1368644{col 30}{space 2} .0096977{col 41}{space 1}   14.11{col 50}{space 3}0.000{col 58}{space 4} .1178572{col 71}{space 3} .1558716
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0390978{col 30}{space 2} .0100684{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0193641{col 71}{space 3} .0588314
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0059782{col 30}{space 2} .0086979{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.0230259{col 71}{space 3} .0110694
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0123682{col 30}{space 2} .0030843{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.0184134{col 71}{space 3}-.0063231
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0943795{col 30}{space 2} .0051598{col 41}{space 1}  -18.29{col 50}{space 3}0.000{col 58}{space 4}-.1044926{col 71}{space 3}-.0842664
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0767884{col 30}{space 2} .0052051{col 41}{space 1}  -14.75{col 50}{space 3}0.000{col 58}{space 4}-.0869902{col 71}{space 3}-.0665866
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0519985{col 30}{space 2} .0050471{col 41}{space 1}  -10.30{col 50}{space 3}0.000{col 58}{space 4}-.0618907{col 71}{space 3}-.0421063
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.503852{col 30}{space 2}  .013381{col 41}{space 1}  112.39{col 50}{space 3}0.000{col 58}{space 4} 1.477626{col 71}{space 3} 1.530079
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    18,592
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .099243{col 30}{space 2} .0146116{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .0706048{col 71}{space 3} .1278813
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0296303{col 30}{space 2}  .004708{col 41}{space 1}   -6.29{col 50}{space 3}0.000{col 58}{space 4}-.0388578{col 71}{space 3}-.0204028
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1253531{col 30}{space 2} .0511621{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0250771{col 71}{space 3}  .225629
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0050699{col 30}{space 2} .0009412{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0032252{col 71}{space 3} .0069146
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3096467{col 30}{space 2} .0350206{col 41}{space 1}    8.84{col 50}{space 3}0.000{col 58}{space 4} .2410075{col 71}{space 3} .3782859
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2592545{col 30}{space 2} .0303089{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .1998502{col 71}{space 3} .3186587
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0428409{col 30}{space 2} .0390901{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0337743{col 71}{space 3} .1194561
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2177719{col 30}{space 2} .0420964{col 41}{space 1}    5.17{col 50}{space 3}0.000{col 58}{space 4} .1352645{col 71}{space 3} .3002794
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0847617{col 30}{space 2}  .044881{col 41}{space 1}    1.89{col 50}{space 3}0.059{col 58}{space 4}-.0032034{col 71}{space 3} .1727267
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2042183{col 30}{space 2} .0453821{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .1152709{col 71}{space 3} .2931656
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .288777{col 30}{space 2} .0397904{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .2107891{col 71}{space 3} .3667648
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0421585{col 30}{space 2}  .051376{col 41}{space 1}   -0.82{col 50}{space 3}0.412{col 58}{space 4}-.1428536{col 71}{space 3} .0585365
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0171074{col 30}{space 2} .0107626{col 41}{space 1}   -1.59{col 50}{space 3}0.112{col 58}{space 4}-.0382017{col 71}{space 3}  .003987
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .379222{col 30}{space 2} .0590872{col 41}{space 1}    6.42{col 50}{space 3}0.000{col 58}{space 4} .2634132{col 71}{space 3} .4950308
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0454504{col 30}{space 2} .0537185{col 41}{space 1}   -0.85{col 50}{space 3}0.398{col 58}{space 4}-.1507366{col 71}{space 3} .0598359
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .953827{col 30}{space 2} .0639389{col 41}{space 1}   14.92{col 50}{space 3}0.000{col 58}{space 4}  .828509{col 71}{space 3} 1.079145
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8182565{col 30}{space 2} .0579701{col 41}{space 1}   14.12{col 50}{space 3}0.000{col 58}{space 4} .7046371{col 71}{space 3} .9318759
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2337495{col 30}{space 2} .0601895{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .1157803{col 71}{space 3} .3517188
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0357414{col 30}{space 2} .0520029{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.1376653{col 71}{space 3} .0661824
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0739445{col 30}{space 2} .0184418{col 41}{space 1}   -4.01{col 50}{space 3}0.000{col 58}{space 4}-.1100899{col 71}{space 3}-.0377991
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5642564{col 30}{space 2} .0307042{col 41}{space 1}  -18.38{col 50}{space 3}0.000{col 58}{space 4}-.6244355{col 71}{space 3}-.5040774
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4590863{col 30}{space 2} .0309786{col 41}{space 1}  -14.82{col 50}{space 3}0.000{col 58}{space 4}-.5198032{col 71}{space 3}-.3983694
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3108777{col 30}{space 2} .0300963{col 41}{space 1}  -10.33{col 50}{space 3}0.000{col 58}{space 4}-.3698655{col 71}{space 3}  -.25189
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-42164.636}  
Iteration 1:{space 3}log pseudolikelihood = {res:-42164.636}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    21,117
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   3823.50
{txt}Log pseudolikelihood = {res}-42164.636{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:10,363} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0245285{col 30}{space 2} .0018769{col 41}{space 1}   13.07{col 50}{space 3}0.000{col 58}{space 4} .0208498{col 71}{space 3} .0282072
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0013753{col 30}{space 2} .0007679{col 41}{space 1}   -1.79{col 50}{space 3}0.073{col 58}{space 4}-.0028804{col 71}{space 3} .0001297
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .006214{col 30}{space 2}  .009101{col 41}{space 1}    0.68{col 50}{space 3}0.495{col 58}{space 4}-.0116236{col 71}{space 3} .0240517
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0000318{col 30}{space 2}  .000145{col 41}{space 1}   -0.22{col 50}{space 3}0.827{col 58}{space 4}-.0003159{col 71}{space 3} .0002524
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0139124{col 30}{space 2} .0048115{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0044821{col 71}{space 3} .0233427
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0635861{col 30}{space 2} .0053822{col 41}{space 1}   11.81{col 50}{space 3}0.000{col 58}{space 4} .0530371{col 71}{space 3}  .074135
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0247707{col 30}{space 2}  .009055{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0070233{col 71}{space 3} .0425181
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0585333{col 30}{space 2}  .007177{col 41}{space 1}    8.16{col 50}{space 3}0.000{col 58}{space 4} .0444666{col 71}{space 3}    .0726
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0112299{col 30}{space 2} .0070635{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.0026143{col 71}{space 3} .0250742
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0250327{col 30}{space 2} .0051328{col 41}{space 1}    4.88{col 50}{space 3}0.000{col 58}{space 4} .0149726{col 71}{space 3} .0350928
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0452178{col 30}{space 2} .0053971{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .0346397{col 71}{space 3} .0557959
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0330609{col 30}{space 2} .0047913{col 41}{space 1}   -6.90{col 50}{space 3}0.000{col 58}{space 4}-.0424517{col 71}{space 3}-.0236702
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0000592{col 30}{space 2} .0003941{col 41}{space 1}    0.15{col 50}{space 3}0.881{col 58}{space 4}-.0007133{col 71}{space 3} .0008316
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .007962{col 30}{space 2} .0051061{col 41}{space 1}    1.56{col 50}{space 3}0.119{col 58}{space 4}-.0020459{col 71}{space 3} .0179698
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0723489{col 30}{space 2} .0115739{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .0496644{col 71}{space 3} .0950334
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0820909{col 30}{space 2}    .0098{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .0628833{col 71}{space 3} .1012985
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .094772{col 30}{space 2} .0090555{col 41}{space 1}   10.47{col 50}{space 3}0.000{col 58}{space 4} .0770235{col 71}{space 3} .1125206
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0150482{col 30}{space 2} .0072351{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0008675{col 71}{space 3} .0292288
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0359376{col 30}{space 2} .0073929{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .0214477{col 71}{space 3} .0504275
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0167663{col 30}{space 2} .0022437{col 41}{space 1}   -7.47{col 50}{space 3}0.000{col 58}{space 4}-.0211639{col 71}{space 3}-.0123687
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0311451{col 30}{space 2} .0051428{col 41}{space 1}    6.06{col 50}{space 3}0.000{col 58}{space 4} .0210654{col 71}{space 3} .0412247
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0276597{col 30}{space 2}  .004246{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .0193378{col 71}{space 3} .0359817
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0127524{col 30}{space 2} .0045836{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0037687{col 71}{space 3} .0217361
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.487266{col 30}{space 2} .0113693{col 41}{space 1}  130.81{col 50}{space 3}0.000{col 58}{space 4} 1.464983{col 71}{space 3}  1.50955
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    21,117
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1450466{col 30}{space 2} .0110793{col 41}{space 1}   13.09{col 50}{space 3}0.000{col 58}{space 4} .1233316{col 71}{space 3} .1667617
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0081328{col 30}{space 2} .0045418{col 41}{space 1}   -1.79{col 50}{space 3}0.073{col 58}{space 4}-.0170346{col 71}{space 3}  .000769
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .036746{col 30}{space 2} .0538158{col 41}{space 1}    0.68{col 50}{space 3}0.495{col 58}{space 4} -.068731{col 71}{space 3}  .142223
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0001878{col 30}{space 2} .0008573{col 41}{space 1}   -0.22{col 50}{space 3}0.827{col 58}{space 4}-.0018681{col 71}{space 3} .0014925
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0822693{col 30}{space 2} .0284513{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0265058{col 71}{space 3} .1380327
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .376009{col 30}{space 2} .0318402{col 41}{space 1}   11.81{col 50}{space 3}0.000{col 58}{space 4} .3136033{col 71}{space 3} .4384146
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1464789{col 30}{space 2} .0535454{col 41}{space 1}    2.74{col 50}{space 3}0.006{col 58}{space 4} .0415319{col 71}{space 3} .2514259
{txt}{space 11}phone {c |}{col 18}{res}{space 2}   .34613{col 30}{space 2} .0424411{col 41}{space 1}    8.16{col 50}{space 3}0.000{col 58}{space 4}  .262947{col 71}{space 3} .4293129
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .066407{col 30}{space 2} .0417685{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.0154576{col 71}{space 3} .1482717
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1480281{col 30}{space 2} .0303509{col 41}{space 1}    4.88{col 50}{space 3}0.000{col 58}{space 4} .0885413{col 71}{space 3} .2075149
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2673904{col 30}{space 2} .0319133{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .2048415{col 71}{space 3} .3299392
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.195502{col 30}{space 2} .0283254{col 41}{space 1}   -6.90{col 50}{space 3}0.000{col 58}{space 4}-.2510188{col 71}{space 3}-.1399852
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003498{col 30}{space 2} .0023306{col 41}{space 1}    0.15{col 50}{space 3}0.881{col 58}{space 4}-.0042181{col 71}{space 3} .0049177
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0470821{col 30}{space 2} .0301971{col 41}{space 1}    1.56{col 50}{space 3}0.119{col 58}{space 4} -.012103{col 71}{space 3} .1062673
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4278272{col 30}{space 2} .0684387{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .2936898{col 71}{space 3} .5619646
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4854353{col 30}{space 2} .0579468{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .3718617{col 71}{space 3} .5990089
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5604235{col 30}{space 2}  .053507{col 41}{space 1}   10.47{col 50}{space 3}0.000{col 58}{space 4} .4555517{col 71}{space 3} .6652954
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0889856{col 30}{space 2} .0427854{col 41}{space 1}    2.08{col 50}{space 3}0.038{col 58}{space 4} .0051277{col 71}{space 3} .1728435
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2125127{col 30}{space 2} .0437122{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .1268384{col 71}{space 3}  .298187
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0991457{col 30}{space 2} .0132591{col 41}{space 1}   -7.48{col 50}{space 3}0.000{col 58}{space 4}-.1251331{col 71}{space 3}-.0731584
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .1841728{col 30}{space 2} .0304321{col 41}{space 1}    6.05{col 50}{space 3}0.000{col 58}{space 4} .1245269{col 71}{space 3} .2438186
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .1635627{col 30}{space 2} .0251086{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .1143507{col 71}{space 3} .2127746
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}   .07541{col 30}{space 2} .0270968{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0223012{col 71}{space 3} .1285187
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. poisson hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-40490.522}  
Iteration 1:{space 3}log pseudolikelihood = {res:-40490.522}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    20,313
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   2904.88
{txt}Log pseudolikelihood = {res}-40490.522{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,107} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0174045{col 30}{space 2} .0017713{col 41}{space 1}    9.83{col 50}{space 3}0.000{col 58}{space 4} .0139328{col 71}{space 3} .0208761
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0021644{col 30}{space 2} .0009151{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0003708{col 71}{space 3}  .003958
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0245223{col 30}{space 2} .0106785{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0035929{col 71}{space 3} .0454518
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003855{col 30}{space 2} .0001773{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.0007331{col 71}{space 3}-.0000379
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0141352{col 30}{space 2} .0058154{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0027372{col 71}{space 3} .0255332
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0670365{col 30}{space 2}  .006055{col 41}{space 1}   11.07{col 50}{space 3}0.000{col 58}{space 4} .0551689{col 71}{space 3} .0789041
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0337329{col 30}{space 2} .0080077{col 41}{space 1}    4.21{col 50}{space 3}0.000{col 58}{space 4} .0180382{col 71}{space 3} .0494277
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0472196{col 30}{space 2}  .006333{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .0348071{col 71}{space 3} .0596321
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0554553{col 30}{space 2} .0057693{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4} .0441476{col 71}{space 3}  .066763
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0105266{col 30}{space 2} .0048994{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4}  .000924{col 71}{space 3} .0201292
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0347536{col 30}{space 2} .0049918{col 41}{space 1}    6.96{col 50}{space 3}0.000{col 58}{space 4} .0249699{col 71}{space 3} .0445373
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0150868{col 30}{space 2}  .004671{col 41}{space 1}   -3.23{col 50}{space 3}0.001{col 58}{space 4}-.0242419{col 71}{space 3}-.0059318
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003664{col 30}{space 2} .0002425{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4} -.000109{col 71}{space 3} .0008417
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0048239{col 30}{space 2} .0051946{col 41}{space 1}   -0.93{col 50}{space 3}0.353{col 58}{space 4}-.0150052{col 71}{space 3} .0053574
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0270432{col 30}{space 2} .0125837{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0023796{col 71}{space 3} .0517067
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0696662{col 30}{space 2} .0110845{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4}  .047941{col 71}{space 3} .0913914
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .083896{col 30}{space 2} .0106107{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .0630994{col 71}{space 3} .1046926
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0261996{col 30}{space 2}  .009261{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0080483{col 71}{space 3} .0443509
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0607379{col 30}{space 2} .0089205{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .0432541{col 71}{space 3} .0782217
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0010574{col 30}{space 2} .0025765{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-.0061072{col 71}{space 3} .0039924
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0327141{col 30}{space 2} .0062213{col 41}{space 1}   -5.26{col 50}{space 3}0.000{col 58}{space 4}-.0449077{col 71}{space 3}-.0205206
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0133942{col 30}{space 2} .0057198{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.0246047{col 71}{space 3}-.0021837
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0552727{col 30}{space 2} .0054365{col 41}{space 1}   10.17{col 50}{space 3}0.000{col 58}{space 4} .0446174{col 71}{space 3}  .065928
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0122442{col 30}{space 2} .0055253{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0014147{col 71}{space 3} .0230736
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0468248{col 30}{space 2} .0051639{col 41}{space 1}    9.07{col 50}{space 3}0.000{col 58}{space 4} .0367037{col 71}{space 3} .0569458
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.429168{col 30}{space 2} .0150237{col 41}{space 1}   95.13{col 50}{space 3}0.000{col 58}{space 4} 1.399722{col 71}{space 3} 1.458614
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    20,313
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .098603{col 30}{space 2} .0100278{col 41}{space 1}    9.83{col 50}{space 3}0.000{col 58}{space 4} .0789487{col 71}{space 3} .1182572
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0122622{col 30}{space 2} .0051846{col 41}{space 1}    2.37{col 50}{space 3}0.018{col 58}{space 4} .0021005{col 71}{space 3}  .022424
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1389285{col 30}{space 2} .0604872{col 41}{space 1}    2.30{col 50}{space 3}0.022{col 58}{space 4} .0203758{col 71}{space 3} .2574812
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0021841{col 30}{space 2} .0010048{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.0041534{col 71}{space 3}-.0002147
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0800815{col 30}{space 2} .0329397{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0155208{col 71}{space 3} .1446422
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3797877{col 30}{space 2}  .034277{col 41}{space 1}   11.08{col 50}{space 3}0.000{col 58}{space 4} .3126061{col 71}{space 3} .4469694
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1911102{col 30}{space 2}  .045357{col 41}{space 1}    4.21{col 50}{space 3}0.000{col 58}{space 4}  .102212{col 71}{space 3} .2800083
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2675172{col 30}{space 2} .0358608{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .1972314{col 71}{space 3} .3378031
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3141758{col 30}{space 2} .0326775{col 41}{space 1}    9.61{col 50}{space 3}0.000{col 58}{space 4}  .250129{col 71}{space 3} .3782226
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0596371{col 30}{space 2} .0277618{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0052249{col 71}{space 3} .1140493
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1968926{col 30}{space 2} .0282883{col 41}{space 1}    6.96{col 50}{space 3}0.000{col 58}{space 4} .1414486{col 71}{space 3} .2523367
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0854728{col 30}{space 2} .0264649{col 41}{space 1}   -3.23{col 50}{space 3}0.001{col 58}{space 4}-.1373431{col 71}{space 3}-.0336025
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0020756{col 30}{space 2} .0013741{col 41}{space 1}    1.51{col 50}{space 3}0.131{col 58}{space 4}-.0006177{col 71}{space 3} .0047688
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0273295{col 30}{space 2} .0294289{col 41}{space 1}   -0.93{col 50}{space 3}0.353{col 58}{space 4}-.0850091{col 71}{space 3} .0303501
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}   .15321{col 30}{space 2} .0712892{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0134857{col 71}{space 3} .2929343
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3946861{col 30}{space 2} .0627369{col 41}{space 1}    6.29{col 50}{space 3}0.000{col 58}{space 4}  .271724{col 71}{space 3} .5176482
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4753031{col 30}{space 2} .0600715{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .3575652{col 71}{space 3}  .593041
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1484307{col 30}{space 2} .0524832{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0455654{col 71}{space 3}  .251296
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3441038{col 30}{space 2}  .050539{col 41}{space 1}    6.81{col 50}{space 3}0.000{col 58}{space 4} .2450491{col 71}{space 3} .4431585
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0059905{col 30}{space 2} .0145974{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-.0346009{col 71}{space 3} .0226199
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1853382{col 30}{space 2} .0352141{col 41}{space 1}   -5.26{col 50}{space 3}0.000{col 58}{space 4}-.2543566{col 71}{space 3}-.1163199
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0758833{col 30}{space 2} .0324057{col 41}{space 1}   -2.34{col 50}{space 3}0.019{col 58}{space 4}-.1393974{col 71}{space 3}-.0123692
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3131411{col 30}{space 2} .0307756{col 41}{space 1}   10.17{col 50}{space 3}0.000{col 58}{space 4} .2528221{col 71}{space 3} .3734601
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0693679{col 30}{space 2} .0312996{col 41}{space 1}    2.22{col 50}{space 3}0.027{col 58}{space 4} .0080219{col 71}{space 3} .1307139
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2652805{col 30}{space 2} .0292635{col 41}{space 1}    9.07{col 50}{space 3}0.000{col 58}{space 4} .2079251{col 71}{space 3} .3226359
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S21_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean  )
{res}{txt}(note: file S21_poisson.rtf not found)
(output written to {browse  `"S21_poisson.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                                   S22                                        *
. ********************************************************************************
. preserve
{txt}
{com}. eststo clear
{txt}
{com}. drop if hdd9_own==.|hdd9_purchase==.
{txt}(7,192 observations deleted)

{com}. drop  pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. foreach x of varlist pdd9 hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. eststo clear
{txt}
{com}. poisson hdd9_own  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-113817.26}  
Iteration 1:{space 3}log pseudolikelihood = {res:-113808.06}  
Iteration 2:{space 3}log pseudolikelihood = {res:-113808.06}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    82,550
{txt}{col 49}Wald chi2({res}35{txt}){col 67}= {res}  43909.98
{txt}Log pseudolikelihood = {res}-113808.06{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1206382{col 30}{space 2} .0029353{col 41}{space 1}   41.10{col 50}{space 3}0.000{col 58}{space 4} .1148851{col 71}{space 3} .1263914
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0072343{col 30}{space 2} .0011324{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .0050147{col 71}{space 3} .0094538
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}   .03718{col 30}{space 2} .0133146{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0110838{col 71}{space 3} .0632762
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004618{col 30}{space 2} .0002114{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0000475{col 71}{space 3} .0008761
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0421265{col 30}{space 2} .0079836{col 41}{space 1}   -5.28{col 50}{space 3}0.000{col 58}{space 4}-.0577741{col 71}{space 3} -.026479
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0042127{col 30}{space 2} .0068864{col 41}{space 1}    0.61{col 50}{space 3}0.541{col 58}{space 4}-.0092843{col 71}{space 3} .0177097
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0012367{col 30}{space 2} .0125033{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-.0257427{col 71}{space 3} .0232694
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0028136{col 30}{space 2} .0076834{col 41}{space 1}   -0.37{col 50}{space 3}0.714{col 58}{space 4}-.0178728{col 71}{space 3} .0122457
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0504742{col 30}{space 2} .0103261{col 41}{space 1}   -4.89{col 50}{space 3}0.000{col 58}{space 4}-.0707131{col 71}{space 3}-.0302354
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} -.036392{col 30}{space 2} .0077796{col 41}{space 1}   -4.68{col 50}{space 3}0.000{col 58}{space 4}-.0516397{col 71}{space 3}-.0211443
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0073364{col 30}{space 2} .0075508{col 41}{space 1}    0.97{col 50}{space 3}0.331{col 58}{space 4}-.0074629{col 71}{space 3} .0221357
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}   .01827{col 30}{space 2} .0062573{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0060059{col 71}{space 3} .0305342
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0026801{col 30}{space 2}  .000495{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4}   .00171{col 71}{space 3} .0036502
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .053546{col 30}{space 2} .0068588{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4}  .040103{col 71}{space 3}  .066989
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1440688{col 30}{space 2} .0181297{col 41}{space 1}    7.95{col 50}{space 3}0.000{col 58}{space 4} .1085351{col 71}{space 3} .1796024
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0433803{col 30}{space 2} .0118427{col 41}{space 1}   -3.66{col 50}{space 3}0.000{col 58}{space 4}-.0665915{col 71}{space 3}-.0201691
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2462427{col 30}{space 2} .0152072{col 41}{space 1}  -16.19{col 50}{space 3}0.000{col 58}{space 4}-.2760483{col 71}{space 3}-.2164372
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1307254{col 30}{space 2} .0128085{col 41}{space 1}  -10.21{col 50}{space 3}0.000{col 58}{space 4}-.1558295{col 71}{space 3}-.1056212
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1622131{col 30}{space 2} .0112574{col 41}{space 1}  -14.41{col 50}{space 3}0.000{col 58}{space 4}-.1842772{col 71}{space 3}-.1401491
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2399799{col 30}{space 2} .0038597{col 41}{space 1}   62.18{col 50}{space 3}0.000{col 58}{space 4}  .232415{col 71}{space 3} .2475449
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} .3755953{col 30}{space 2} .0175633{col 41}{space 1}   21.39{col 50}{space 3}0.000{col 58}{space 4} .3411718{col 71}{space 3} .4100188
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1422905{col 30}{space 2} .0192171{col 41}{space 1}   -7.40{col 50}{space 3}0.000{col 58}{space 4}-.1799554{col 71}{space 3}-.1046257
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} .6483374{col 30}{space 2}  .017088{col 41}{space 1}   37.94{col 50}{space 3}0.000{col 58}{space 4} .6148456{col 71}{space 3} .6818292
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .3666345{col 30}{space 2} .0175832{col 41}{space 1}   20.85{col 50}{space 3}0.000{col 58}{space 4}  .332172{col 71}{space 3}  .401097
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .4732039{col 30}{space 2} .0193548{col 41}{space 1}   24.45{col 50}{space 3}0.000{col 58}{space 4} .4352691{col 71}{space 3} .5111387
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0980687{col 30}{space 2} .0174593{col 41}{space 1}   -5.62{col 50}{space 3}0.000{col 58}{space 4}-.1322882{col 71}{space 3}-.0638492
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0382878{col 30}{space 2} .0133075{col 41}{space 1}   -2.88{col 50}{space 3}0.004{col 58}{space 4}  -.06437{col 71}{space 3}-.0122056
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1024921{col 30}{space 2} .0156378{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4} .0718425{col 71}{space 3} .1331416
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0150995{col 30}{space 2}  .013439{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.0112406{col 71}{space 3} .0414395
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0786027{col 30}{space 2}  .015705{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .0478215{col 71}{space 3} .1093839
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1272596{col 30}{space 2} .0165569{col 41}{space 1}   -7.69{col 50}{space 3}0.000{col 58}{space 4}-.1597105{col 71}{space 3}-.0948086
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0800881{col 30}{space 2} .0152297{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4} .0502384{col 71}{space 3} .1099378
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.1373774{col 30}{space 2} .0219841{col 41}{space 1}   -6.25{col 50}{space 3}0.000{col 58}{space 4}-.1804653{col 71}{space 3}-.0942894
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2312338{col 30}{space 2} .0160265{col 41}{space 1}   14.43{col 50}{space 3}0.000{col 58}{space 4} .1998225{col 71}{space 3} .2626452
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0082779{col 30}{space 2} .0164058{col 41}{space 1}    0.50{col 50}{space 3}0.614{col 58}{space 4}-.0238769{col 71}{space 3} .0404327
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}-.9082705{col 30}{space 2}  .024538{col 41}{space 1}  -37.01{col 50}{space 3}0.000{col 58}{space 4}-.9563641{col 71}{space 3}-.8601769
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    82,550
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2016054{col 30}{space 2} .0049055{col 41}{space 1}   41.10{col 50}{space 3}0.000{col 58}{space 4} .1919908{col 71}{space 3}   .21122
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0120896{col 30}{space 2} .0018936{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .0083782{col 71}{space 3} .0158009
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0621336{col 30}{space 2} .0222455{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0185333{col 71}{space 3}  .105734
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007717{col 30}{space 2} .0003533{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0000792{col 71}{space 3} .0014642
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0704001{col 30}{space 2} .0133383{col 41}{space 1}   -5.28{col 50}{space 3}0.000{col 58}{space 4}-.0965426{col 71}{space 3}-.0442575
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0070401{col 30}{space 2} .0115085{col 41}{space 1}    0.61{col 50}{space 3}0.541{col 58}{space 4} -.015516{col 71}{space 3} .0295963
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0020667{col 30}{space 2}  .020895{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-.0430201{col 71}{space 3} .0388867
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0047019{col 30}{space 2} .0128402{col 41}{space 1}   -0.37{col 50}{space 3}0.714{col 58}{space 4}-.0298682{col 71}{space 3} .0204644
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0843504{col 30}{space 2} .0172557{col 41}{space 1}   -4.89{col 50}{space 3}0.000{col 58}{space 4} -.118171{col 71}{space 3}-.0505297
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0608167{col 30}{space 2} .0129982{col 41}{space 1}   -4.68{col 50}{space 3}0.000{col 58}{space 4}-.0862928{col 71}{space 3}-.0353407
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0122603{col 30}{space 2} .0126188{col 41}{space 1}    0.97{col 50}{space 3}0.331{col 58}{space 4}-.0124721{col 71}{space 3} .0369927
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0305321{col 30}{space 2} .0104575{col 41}{space 1}    2.92{col 50}{space 3}0.004{col 58}{space 4} .0100358{col 71}{space 3} .0510283
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0044789{col 30}{space 2} .0008275{col 41}{space 1}    5.41{col 50}{space 3}0.000{col 58}{space 4} .0028571{col 71}{space 3} .0061007
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0894838{col 30}{space 2}  .011478{col 41}{space 1}    7.80{col 50}{space 3}0.000{col 58}{space 4} .0669873{col 71}{space 3} .1119803
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2407615{col 30}{space 2} .0303133{col 41}{space 1}    7.94{col 50}{space 3}0.000{col 58}{space 4} .1813485{col 71}{space 3} .3001745
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0724953{col 30}{space 2} .0197912{col 41}{space 1}   -3.66{col 50}{space 3}0.000{col 58}{space 4}-.1112854{col 71}{space 3}-.0337052
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.4115103{col 30}{space 2} .0253978{col 41}{space 1}  -16.20{col 50}{space 3}0.000{col 58}{space 4} -.461289{col 71}{space 3}-.3617316
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2184626{col 30}{space 2} .0214139{col 41}{space 1}  -10.20{col 50}{space 3}0.000{col 58}{space 4}-.2604331{col 71}{space 3}-.1764921
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2710836{col 30}{space 2} .0188251{col 41}{space 1}  -14.40{col 50}{space 3}0.000{col 58}{space 4}-.3079802{col 71}{space 3} -.234187
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .4010441{col 30}{space 2} .0065902{col 41}{space 1}   60.85{col 50}{space 3}0.000{col 58}{space 4} .3881276{col 71}{space 3} .4139606
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}  .521268{col 30}{space 2} .0227223{col 41}{space 1}   22.94{col 50}{space 3}0.000{col 58}{space 4} .4767332{col 71}{space 3} .5658029
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.1516617{col 30}{space 2} .0210491{col 41}{space 1}   -7.21{col 50}{space 3}0.000{col 58}{space 4}-.1929172{col 71}{space 3}-.1104061
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} 1.043271{col 30}{space 2} .0231265{col 41}{space 1}   45.11{col 50}{space 3}0.000{col 58}{space 4} .9979442{col 71}{space 3} 1.088598
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2} .5064171{col 30}{space 2} .0226039{col 41}{space 1}   22.40{col 50}{space 3}0.000{col 58}{space 4} .4621143{col 71}{space 3} .5507199
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .6919574{col 30}{space 2} .0272813{col 41}{space 1}   25.36{col 50}{space 3}0.000{col 58}{space 4} .6384871{col 71}{space 3} .7454278
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.1509624{col 30}{space 2} .0271409{col 41}{space 1}   -5.56{col 50}{space 3}0.000{col 58}{space 4}-.2041576{col 71}{space 3}-.0977671
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0607061{col 30}{space 2}  .021398{col 41}{space 1}   -2.84{col 50}{space 3}0.005{col 58}{space 4}-.1026454{col 71}{space 3}-.0187669
{txt}{space 11}2011  {c |}{col 18}{res}{space 2} .1744198{col 30}{space 2} .0260327{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .1233967{col 71}{space 3} .2254429
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0245869{col 30}{space 2} .0217904{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0181215{col 71}{space 3} .0672953
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1321531{col 30}{space 2} .0259293{col 41}{space 1}    5.10{col 50}{space 3}0.000{col 58}{space 4} .0813327{col 71}{space 3} .1829735
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.193112{col 30}{space 2} .0254084{col 41}{space 1}   -7.60{col 50}{space 3}0.000{col 58}{space 4}-.2429115{col 71}{space 3}-.1433124
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1347518{col 30}{space 2} .0250853{col 41}{space 1}    5.37{col 50}{space 3}0.000{col 58}{space 4} .0855856{col 71}{space 3} .1839181
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2074365{col 30}{space 2} .0327904{col 41}{space 1}   -6.33{col 50}{space 3}0.000{col 58}{space 4}-.2717045{col 71}{space 3}-.1431685
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4204264{col 30}{space 2} .0280092{col 41}{space 1}   15.01{col 50}{space 3}0.000{col 58}{space 4} .3655293{col 71}{space 3} .4753235
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0134332{col 30}{space 2} .0265835{col 41}{space 1}    0.51{col 50}{space 3}0.613{col 58}{space 4}-.0386696{col 71}{space 3}  .065536
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-12952.077}  
Iteration 1:{space 3}log pseudolikelihood = {res:-12945.357}  
Iteration 2:{space 3}log pseudolikelihood = {res:-12945.335}  
Iteration 3:{space 3}log pseudolikelihood = {res:-12945.335}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    10,583
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   5846.44
{txt}Log pseudolikelihood = {res}-12945.335{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .046376{col 30}{space 2} .0065537{col 41}{space 1}    7.08{col 50}{space 3}0.000{col 58}{space 4}  .033531{col 71}{space 3}  .059221
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0177312{col 30}{space 2} .0041432{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0096106{col 71}{space 3} .0258518
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1066359{col 30}{space 2} .0375103{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0331172{col 71}{space 3} .1801547
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .001861{col 30}{space 2} .0005715{col 41}{space 1}    3.26{col 50}{space 3}0.001{col 58}{space 4} .0007409{col 71}{space 3} .0029812
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1290852{col 30}{space 2} .0225441{col 41}{space 1}   -5.73{col 50}{space 3}0.000{col 58}{space 4}-.1732707{col 71}{space 3}-.0848996
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0034839{col 30}{space 2} .0172932{col 41}{space 1}   -0.20{col 50}{space 3}0.840{col 58}{space 4}-.0373779{col 71}{space 3} .0304101
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1171923{col 30}{space 2} .0999324{col 41}{space 1}   -1.17{col 50}{space 3}0.241{col 58}{space 4}-.3130563{col 71}{space 3} .0786717
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0259517{col 30}{space 2} .0205336{col 41}{space 1}    1.26{col 50}{space 3}0.206{col 58}{space 4}-.0142935{col 71}{space 3} .0661968
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1329721{col 30}{space 2} .0301945{col 41}{space 1}   -4.40{col 50}{space 3}0.000{col 58}{space 4}-.1921522{col 71}{space 3} -.073792
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0219397{col 30}{space 2} .0506517{col 41}{space 1}   -0.43{col 50}{space 3}0.665{col 58}{space 4}-.1212152{col 71}{space 3} .0773358
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0131135{col 30}{space 2} .0296708{col 41}{space 1}   -0.44{col 50}{space 3}0.659{col 58}{space 4}-.0712672{col 71}{space 3} .0450402
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0210914{col 30}{space 2} .0178865{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.0561483{col 71}{space 3} .0139655
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0101263{col 30}{space 2} .0035312{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0032052{col 71}{space 3} .0170473
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0092125{col 30}{space 2} .0171104{col 41}{space 1}   -0.54{col 50}{space 3}0.590{col 58}{space 4}-.0427483{col 71}{space 3} .0243233
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3315411{col 30}{space 2} .1703988{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4}-.0024344{col 71}{space 3} .6655165
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0733063{col 30}{space 2}  .030908{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.1338848{col 71}{space 3}-.0127277
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3436265{col 30}{space 2} .0443091{col 41}{space 1}   -7.76{col 50}{space 3}0.000{col 58}{space 4}-.4304706{col 71}{space 3}-.2567823
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.6988977{col 30}{space 2} .0898167{col 41}{space 1}   -7.78{col 50}{space 3}0.000{col 58}{space 4}-.8749352{col 71}{space 3}-.5228603
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1735489{col 30}{space 2} .0380281{col 41}{space 1}   -4.56{col 50}{space 3}0.000{col 58}{space 4}-.2480825{col 71}{space 3}-.0990152
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2088759{col 30}{space 2} .0085069{col 41}{space 1}   24.55{col 50}{space 3}0.000{col 58}{space 4} .1922026{col 71}{space 3} .2255491
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1201039{col 30}{space 2} .0128266{col 41}{space 1}   -9.36{col 50}{space 3}0.000{col 58}{space 4}-.1452436{col 71}{space 3}-.0949642
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} -.502779{col 30}{space 2} .0443869{col 41}{space 1}  -11.33{col 50}{space 3}0.000{col 58}{space 4}-.5897757{col 71}{space 3}-.4157823
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    10,583
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0643953{col 30}{space 2} .0090816{col 41}{space 1}    7.09{col 50}{space 3}0.000{col 58}{space 4} .0465958{col 71}{space 3} .0821948
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0246206{col 30}{space 2} .0057602{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0133308{col 71}{space 3} .0359104
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1480691{col 30}{space 2} .0521124{col 41}{space 1}    2.84{col 50}{space 3}0.004{col 58}{space 4} .0459307{col 71}{space 3} .2502075
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0025841{col 30}{space 2} .0007945{col 41}{space 1}    3.25{col 50}{space 3}0.001{col 58}{space 4}  .001027{col 71}{space 3} .0041413
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1792409{col 30}{space 2} .0312333{col 41}{space 1}   -5.74{col 50}{space 3}0.000{col 58}{space 4}-.2404572{col 71}{space 3}-.1180247
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0048376{col 30}{space 2} .0240119{col 41}{space 1}   -0.20{col 50}{space 3}0.840{col 58}{space 4}-.0519001{col 71}{space 3} .0422249
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1627271{col 30}{space 2} .1388364{col 41}{space 1}   -1.17{col 50}{space 3}0.241{col 58}{space 4}-.4348415{col 71}{space 3} .1093873
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0360351{col 30}{space 2} .0285211{col 41}{space 1}    1.26{col 50}{space 3}0.206{col 58}{space 4}-.0198652{col 71}{space 3} .0919355
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1846381{col 30}{space 2} .0419163{col 41}{space 1}   -4.40{col 50}{space 3}0.000{col 58}{space 4}-.2667926{col 71}{space 3}-.1024836
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0304643{col 30}{space 2} .0703361{col 41}{space 1}   -0.43{col 50}{space 3}0.665{col 58}{space 4}-.1683204{col 71}{space 3} .1073919
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0182087{col 30}{space 2} .0411999{col 41}{space 1}   -0.44{col 50}{space 3}0.659{col 58}{space 4} -.098959{col 71}{space 3} .0625415
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0292864{col 30}{space 2} .0248418{col 41}{space 1}   -1.18{col 50}{space 3}0.238{col 58}{space 4}-.0779755{col 71}{space 3} .0194027
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0140608{col 30}{space 2} .0049169{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0044239{col 71}{space 3} .0236977
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0127919{col 30}{space 2} .0237526{col 41}{space 1}   -0.54{col 50}{space 3}0.590{col 58}{space 4}-.0593461{col 71}{space 3} .0337622
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4603606{col 30}{space 2} .2367627{col 41}{space 1}    1.94{col 50}{space 3}0.052{col 58}{space 4}-.0036858{col 71}{space 3} .9244069
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1017893{col 30}{space 2} .0429333{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4} -.185937{col 71}{space 3}-.0176415
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.4771417{col 30}{space 2} .0615366{col 41}{space 1}   -7.75{col 50}{space 3}0.000{col 58}{space 4}-.5977512{col 71}{space 3}-.3565322
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.9704528{col 30}{space 2} .1244176{col 41}{space 1}   -7.80{col 50}{space 3}0.000{col 58}{space 4}-1.214307{col 71}{space 3}-.7265987
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2409809{col 30}{space 2}   .05275{col 41}{space 1}   -4.57{col 50}{space 3}0.000{col 58}{space 4}-.3443689{col 71}{space 3}-.1375928
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2900341{col 30}{space 2} .0121457{col 41}{space 1}   23.88{col 50}{space 3}0.000{col 58}{space 4} .2662289{col 71}{space 3} .3138392
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  -.16677{col 30}{space 2} .0178684{col 41}{space 1}   -9.33{col 50}{space 3}0.000{col 58}{space 4}-.2017915{col 71}{space 3}-.1317485
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-13189.497}  
Iteration 1:{space 3}log pseudolikelihood = {res:-13188.882}  
Iteration 2:{space 3}log pseudolikelihood = {res:-13188.882}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     9,155
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   4896.73
{txt}Log pseudolikelihood = {res}-13188.882{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1707362{col 30}{space 2} .0074046{col 41}{space 1}   23.06{col 50}{space 3}0.000{col 58}{space 4} .1562235{col 71}{space 3} .1852489
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0010175{col 30}{space 2} .0041579{col 41}{space 1}    0.24{col 50}{space 3}0.807{col 58}{space 4}-.0071318{col 71}{space 3} .0091668
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.004037{col 30}{space 2} .0366098{col 41}{space 1}   -0.11{col 50}{space 3}0.912{col 58}{space 4}-.0757909{col 71}{space 3} .0677168
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0015734{col 30}{space 2} .0005954{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0004064{col 71}{space 3} .0027404
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0373358{col 30}{space 2} .0213522{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.0791853{col 71}{space 3} .0045137
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .007747{col 30}{space 2} .0207244{col 41}{space 1}    0.37{col 50}{space 3}0.709{col 58}{space 4}-.0328721{col 71}{space 3}  .048366
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1425157{col 30}{space 2} .0657482{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0136517{col 71}{space 3} .2713798
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0117308{col 30}{space 2} .0219553{col 41}{space 1}    0.53{col 50}{space 3}0.593{col 58}{space 4}-.0313008{col 71}{space 3} .0547625
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1233821{col 30}{space 2} .0611273{col 41}{space 1}   -2.02{col 50}{space 3}0.044{col 58}{space 4}-.2431893{col 71}{space 3}-.0035748
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0620856{col 30}{space 2} .0291545{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4}-.1192273{col 71}{space 3}-.0049439
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0295591{col 30}{space 2} .0218004{col 41}{space 1}    1.36{col 50}{space 3}0.175{col 58}{space 4}-.0131689{col 71}{space 3} .0722872
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0047657{col 30}{space 2} .0156439{col 41}{space 1}   -0.30{col 50}{space 3}0.761{col 58}{space 4}-.0354272{col 71}{space 3} .0258958
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0643919{col 30}{space 2} .0114211{col 41}{space 1}    5.64{col 50}{space 3}0.000{col 58}{space 4}  .042007{col 71}{space 3} .0867769
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0479373{col 30}{space 2} .0198414{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4}  .009049{col 71}{space 3} .0868257
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0528308{col 30}{space 2} .0937151{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4}-.2365091{col 71}{space 3} .1308474
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0773819{col 30}{space 2} .0338168{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.1436616{col 71}{space 3}-.0111022
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1126916{col 30}{space 2} .0755412{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-.2607497{col 71}{space 3} .0353664
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0236369{col 30}{space 2}  .042192{col 41}{space 1}   -0.56{col 50}{space 3}0.575{col 58}{space 4}-.1063318{col 71}{space 3}  .059058
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1632063{col 30}{space 2}  .033846{col 41}{space 1}   -4.82{col 50}{space 3}0.000{col 58}{space 4}-.2295434{col 71}{space 3}-.0968693
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2093154{col 30}{space 2} .0109077{col 41}{space 1}   19.19{col 50}{space 3}0.000{col 58}{space 4} .1879367{col 71}{space 3} .2306941
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}   .34107{col 30}{space 2} .0195526{col 41}{space 1}   17.44{col 50}{space 3}0.000{col 58}{space 4} .3027477{col 71}{space 3} .3793924
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .159833{col 30}{space 2} .0167104{col 41}{space 1}    9.56{col 50}{space 3}0.000{col 58}{space 4} .1270812{col 71}{space 3} .1925847
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.6849459{col 30}{space 2} .0468148{col 41}{space 1}  -14.63{col 50}{space 3}0.000{col 58}{space 4}-.7767011{col 71}{space 3}-.5931907
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     9,155
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2908204{col 30}{space 2} .0126649{col 41}{space 1}   22.96{col 50}{space 3}0.000{col 58}{space 4} .2659977{col 71}{space 3}  .315643
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0017332{col 30}{space 2} .0070824{col 41}{space 1}    0.24{col 50}{space 3}0.807{col 58}{space 4}-.0121481{col 71}{space 3} .0156144
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0068764{col 30}{space 2} .0623568{col 41}{space 1}   -0.11{col 50}{space 3}0.912{col 58}{space 4}-.1290934{col 71}{space 3} .1153406
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}   .00268{col 30}{space 2} .0010138{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4}  .000693{col 71}{space 3} .0046669
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0635953{col 30}{space 2} .0363564{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.1348526{col 71}{space 3} .0076621
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0131956{col 30}{space 2} .0353004{col 41}{space 1}    0.37{col 50}{space 3}0.709{col 58}{space 4}-.0559919{col 71}{space 3} .0823832
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2427516{col 30}{space 2} .1119676{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0232991{col 71}{space 3}  .462204
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0199815{col 30}{space 2} .0373985{col 41}{space 1}    0.53{col 50}{space 3}0.593{col 58}{space 4}-.0533182{col 71}{space 3} .0932812
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2101606{col 30}{space 2} .1041327{col 41}{space 1}   -2.02{col 50}{space 3}0.044{col 58}{space 4}-.4142569{col 71}{space 3}-.0060642
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1057523{col 30}{space 2} .0496313{col 41}{space 1}   -2.13{col 50}{space 3}0.033{col 58}{space 4} -.203028{col 71}{space 3}-.0084767
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .050349{col 30}{space 2} .0371464{col 41}{space 1}    1.36{col 50}{space 3}0.175{col 58}{space 4}-.0224566{col 71}{space 3} .1231546
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0081176{col 30}{space 2} .0266453{col 41}{space 1}   -0.30{col 50}{space 3}0.761{col 58}{space 4}-.0603414{col 71}{space 3} .0441062
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1096808{col 30}{space 2} .0195055{col 41}{space 1}    5.62{col 50}{space 3}0.000{col 58}{space 4} .0714507{col 71}{space 3} .1479109
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0816532{col 30}{space 2} .0337837{col 41}{space 1}    2.42{col 50}{space 3}0.016{col 58}{space 4} .0154384{col 71}{space 3}  .147868
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0899884{col 30}{space 2} .1596481{col 41}{space 1}   -0.56{col 50}{space 3}0.573{col 58}{space 4} -.402893{col 71}{space 3} .2229162
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} -.131807{col 30}{space 2} .0576214{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.2447429{col 71}{space 3}-.0188711
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1919512{col 30}{space 2} .1286779{col 41}{space 1}   -1.49{col 50}{space 3}0.136{col 58}{space 4}-.4441552{col 71}{space 3} .0602528
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0402615{col 30}{space 2} .0718669{col 41}{space 1}   -0.56{col 50}{space 3}0.575{col 58}{space 4} -.181118{col 71}{space 3}  .100595
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2779945{col 30}{space 2}  .057788{col 41}{space 1}   -4.81{col 50}{space 3}0.000{col 58}{space 4}-.3912569{col 71}{space 3}-.1647321
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3565335{col 30}{space 2} .0188504{col 41}{space 1}   18.91{col 50}{space 3}0.000{col 58}{space 4} .3195874{col 71}{space 3} .3934797
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .5809553{col 30}{space 2} .0333683{col 41}{space 1}   17.41{col 50}{space 3}0.000{col 58}{space 4} .5155546{col 71}{space 3} .6463561
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .2722485{col 30}{space 2} .0283145{col 41}{space 1}    9.62{col 50}{space 3}0.000{col 58}{space 4} .2167531{col 71}{space 3}  .327744
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-6883.3388}  
Iteration 1:{space 3}log pseudolikelihood = {res:-6872.4491}  
Iteration 2:{space 3}log pseudolikelihood = {res:-6872.4448}  
Iteration 3:{space 3}log pseudolikelihood = {res:-6872.4448}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     7,044
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   3710.56
{txt}Log pseudolikelihood = {res}-6872.4448{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1876185{col 30}{space 2} .0208563{col 41}{space 1}    9.00{col 50}{space 3}0.000{col 58}{space 4} .1467409{col 71}{space 3} .2284961
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0042706{col 30}{space 2}  .004344{col 41}{space 1}    0.98{col 50}{space 3}0.326{col 58}{space 4}-.0042435{col 71}{space 3} .0127847
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0087455{col 30}{space 2} .0709926{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4}-.1303974{col 71}{space 3} .1478885
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025434{col 30}{space 2} .0009618{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.0044285{col 71}{space 3}-.0006584
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1986091{col 30}{space 2} .0454826{col 41}{space 1}   -4.37{col 50}{space 3}0.000{col 58}{space 4}-.2877533{col 71}{space 3} -.109465
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0453364{col 30}{space 2} .0293135{col 41}{space 1}    1.55{col 50}{space 3}0.122{col 58}{space 4} -.012117{col 71}{space 3} .1027899
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0094045{col 30}{space 2} .0760884{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4} -.139726{col 71}{space 3}  .158535
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0802611{col 30}{space 2} .0400739{col 41}{space 1}   -2.00{col 50}{space 3}0.045{col 58}{space 4}-.1588044{col 71}{space 3}-.0017177
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2050084{col 30}{space 2} .1183922{col 41}{space 1}   -1.73{col 50}{space 3}0.083{col 58}{space 4}-.4370528{col 71}{space 3} .0270359
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0743401{col 30}{space 2} .0602487{col 41}{space 1}    1.23{col 50}{space 3}0.217{col 58}{space 4}-.0437452{col 71}{space 3} .1924254
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0214917{col 30}{space 2} .0389538{col 41}{space 1}   -0.55{col 50}{space 3}0.581{col 58}{space 4}-.0978398{col 71}{space 3} .0548564
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0128029{col 30}{space 2} .0260506{col 41}{space 1}    0.49{col 50}{space 3}0.623{col 58}{space 4}-.0382553{col 71}{space 3} .0638612
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0007777{col 30}{space 2} .0009541{col 41}{space 1}    0.82{col 50}{space 3}0.415{col 58}{space 4}-.0010923{col 71}{space 3} .0026477
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2913029{col 30}{space 2}  .104812{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0858751{col 71}{space 3} .4967306
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0152423{col 30}{space 2} .0982957{col 41}{space 1}   -0.16{col 50}{space 3}0.877{col 58}{space 4}-.2078983{col 71}{space 3} .1774137
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1236823{col 30}{space 2} .0514958{col 41}{space 1}   -2.40{col 50}{space 3}0.016{col 58}{space 4}-.2246122{col 71}{space 3}-.0227525
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.8159985{col 30}{space 2} .1449887{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-1.100171{col 71}{space 3}-.5318259
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.3216036{col 30}{space 2} .0855533{col 41}{space 1}   -3.76{col 50}{space 3}0.000{col 58}{space 4} -.489285{col 71}{space 3}-.1539222
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1019513{col 30}{space 2} .0507539{col 41}{space 1}   -2.01{col 50}{space 3}0.045{col 58}{space 4}-.2014271{col 71}{space 3}-.0024756
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3439981{col 30}{space 2} .0252626{col 41}{space 1}   13.62{col 50}{space 3}0.000{col 58}{space 4} .2944843{col 71}{space 3}  .393512
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .3642873{col 30}{space 2} .0241589{col 41}{space 1}   15.08{col 50}{space 3}0.000{col 58}{space 4} .3169368{col 71}{space 3} .4116378
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-1.266052{col 30}{space 2}  .072445{col 41}{space 1}  -17.48{col 50}{space 3}0.000{col 58}{space 4}-1.408042{col 71}{space 3}-1.124062
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     7,044
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1578403{col 30}{space 2} .0177247{col 41}{space 1}    8.91{col 50}{space 3}0.000{col 58}{space 4} .1231005{col 71}{space 3} .1925802
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0035928{col 30}{space 2} .0036529{col 41}{space 1}    0.98{col 50}{space 3}0.325{col 58}{space 4}-.0035668{col 71}{space 3} .0107524
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0073575{col 30}{space 2} .0597269{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4}-.1097051{col 71}{space 3} .1244201
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0021398{col 30}{space 2} .0008085{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-.0037244{col 71}{space 3}-.0005551
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1670866{col 30}{space 2}  .038316{col 41}{space 1}   -4.36{col 50}{space 3}0.000{col 58}{space 4}-.2421845{col 71}{space 3}-.0919886
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0381408{col 30}{space 2} .0246731{col 41}{space 1}    1.55{col 50}{space 3}0.122{col 58}{space 4}-.0102177{col 71}{space 3} .0864992
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0079118{col 30}{space 2} .0640112{col 41}{space 1}    0.12{col 50}{space 3}0.902{col 58}{space 4}-.1175478{col 71}{space 3} .1333714
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0675223{col 30}{space 2}  .033706{col 41}{space 1}   -2.00{col 50}{space 3}0.045{col 58}{space 4}-.1335849{col 71}{space 3}-.0014597
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1724702{col 30}{space 2} .0996253{col 41}{space 1}   -1.73{col 50}{space 3}0.083{col 58}{space 4}-.3677323{col 71}{space 3} .0227919
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0625411{col 30}{space 2} .0507016{col 41}{space 1}    1.23{col 50}{space 3}0.217{col 58}{space 4}-.0368323{col 71}{space 3} .1619145
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0180806{col 30}{space 2}  .032772{col 41}{space 1}   -0.55{col 50}{space 3}0.581{col 58}{space 4}-.0823125{col 71}{space 3} .0461513
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0107709{col 30}{space 2} .0219205{col 41}{space 1}    0.49{col 50}{space 3}0.623{col 58}{space 4}-.0321925{col 71}{space 3} .0537343
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0006543{col 30}{space 2} .0008027{col 41}{space 1}    0.82{col 50}{space 3}0.415{col 58}{space 4}-.0009191{col 71}{space 3} .0022276
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2450682{col 30}{space 2} .0882257{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0721491{col 71}{space 3} .4179874
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0128231{col 30}{space 2} .0826954{col 41}{space 1}   -0.16{col 50}{space 3}0.877{col 58}{space 4}-.1749032{col 71}{space 3}  .149257
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1040519{col 30}{space 2} .0432893{col 41}{space 1}   -2.40{col 50}{space 3}0.016{col 58}{space 4}-.1888974{col 71}{space 3}-.0192064
{txt}electricity_mean {c |}{col 18}{res}{space 2} -.686486{col 30}{space 2} .1218808{col 41}{space 1}   -5.63{col 50}{space 3}0.000{col 58}{space 4}-.9253679{col 71}{space 3} -.447604
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2705598{col 30}{space 2} .0719851{col 41}{space 1}   -3.76{col 50}{space 3}0.000{col 58}{space 4}-.4116479{col 71}{space 3}-.1294716
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  -.08577{col 30}{space 2} .0427044{col 41}{space 1}   -2.01{col 50}{space 3}0.045{col 58}{space 4} -.169469{col 71}{space 3}-.0020709
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2893999{col 30}{space 2} .0216965{col 41}{space 1}   13.34{col 50}{space 3}0.000{col 58}{space 4} .2468755{col 71}{space 3} .3319243
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .3064688{col 30}{space 2} .0205345{col 41}{space 1}   14.92{col 50}{space 3}0.000{col 58}{space 4}  .266222{col 71}{space 3} .3467157
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-22958.995}  
Iteration 1:{space 3}log pseudolikelihood = {res:-22957.797}  
Iteration 2:{space 3}log pseudolikelihood = {res:-22957.792}  
Iteration 3:{space 3}log pseudolikelihood = {res:-22957.792}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    18,429
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   6598.17
{txt}Log pseudolikelihood = {res}-22957.792{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .179057{col 30}{space 2} .0091607{col 41}{space 1}   19.55{col 50}{space 3}0.000{col 58}{space 4} .1611023{col 71}{space 3} .1970117
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0094046{col 30}{space 2} .0024455{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0046116{col 71}{space 3} .0141976
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0346977{col 30}{space 2} .0307519{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.0949703{col 71}{space 3}  .025575
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0008717{col 30}{space 2}  .000492{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4}-.0000927{col 71}{space 3}  .001836
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} -.057236{col 30}{space 2} .0240169{col 41}{space 1}   -2.38{col 50}{space 3}0.017{col 58}{space 4}-.1043082{col 71}{space 3}-.0101637
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0462957{col 30}{space 2} .0151758{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.0760397{col 71}{space 3}-.0165516
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0446717{col 30}{space 2} .0212096{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4}-.0862417{col 71}{space 3}-.0031017
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0252911{col 30}{space 2} .0197746{col 41}{space 1}    1.28{col 50}{space 3}0.201{col 58}{space 4}-.0134663{col 71}{space 3} .0640486
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0227246{col 30}{space 2} .0307452{col 41}{space 1}   -0.74{col 50}{space 3}0.460{col 58}{space 4}-.0829841{col 71}{space 3} .0375349
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0041707{col 30}{space 2} .0333951{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4}-.0612824{col 71}{space 3} .0696238
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0108371{col 30}{space 2} .0233214{col 41}{space 1}    0.46{col 50}{space 3}0.642{col 58}{space 4} -.034872{col 71}{space 3} .0565462
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0923139{col 30}{space 2} .0233732{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .0465033{col 71}{space 3} .1381245
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0087952{col 30}{space 2} .0026291{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0036422{col 71}{space 3} .0139481
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1249341{col 30}{space 2} .0308403{col 41}{space 1}    4.05{col 50}{space 3}0.000{col 58}{space 4} .0644883{col 71}{space 3} .1853799
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2243611{col 30}{space 2} .0288864{col 41}{space 1}    7.77{col 50}{space 3}0.000{col 58}{space 4} .1677448{col 71}{space 3} .2809775
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0030806{col 30}{space 2} .0292021{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.0603158{col 71}{space 3} .0541545
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.2665126{col 30}{space 2}  .036568{col 41}{space 1}   -7.29{col 50}{space 3}0.000{col 58}{space 4}-.3381847{col 71}{space 3}-.1948406
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2370343{col 30}{space 2}  .044219{col 41}{space 1}   -5.36{col 50}{space 3}0.000{col 58}{space 4} -.323702{col 71}{space 3}-.1503666
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1645886{col 30}{space 2}  .029009{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.2214451{col 71}{space 3}-.1077321
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .197703{col 30}{space 2} .0112355{col 41}{space 1}   17.60{col 50}{space 3}0.000{col 58}{space 4} .1756817{col 71}{space 3} .2197242
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.4180987{col 30}{space 2} .0186846{col 41}{space 1}  -22.38{col 50}{space 3}0.000{col 58}{space 4}-.4547198{col 71}{space 3}-.3814776
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.2121956{col 30}{space 2} .0168018{col 41}{space 1}  -12.63{col 50}{space 3}0.000{col 58}{space 4}-.2451266{col 71}{space 3}-.1792646
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.2228824{col 30}{space 2} .0173774{col 41}{space 1}  -12.83{col 50}{space 3}0.000{col 58}{space 4}-.2569414{col 71}{space 3}-.1888233
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.3429279{col 30}{space 2}  .039969{col 41}{space 1}   -8.58{col 50}{space 3}0.000{col 58}{space 4}-.4212657{col 71}{space 3}-.2645902
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    18,429
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2195923{col 30}{space 2} .0112658{col 41}{space 1}   19.49{col 50}{space 3}0.000{col 58}{space 4} .1975117{col 71}{space 3} .2416729
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0115337{col 30}{space 2}  .003001{col 41}{space 1}    3.84{col 50}{space 3}0.000{col 58}{space 4} .0056518{col 71}{space 3} .0174155
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0425526{col 30}{space 2} .0377229{col 41}{space 1}   -1.13{col 50}{space 3}0.259{col 58}{space 4}-.1164881{col 71}{space 3} .0313829
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .001069{col 30}{space 2} .0006037{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0001143{col 71}{space 3} .0022523
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0701932{col 30}{space 2} .0294161{col 41}{space 1}   -2.39{col 50}{space 3}0.017{col 58}{space 4}-.1278476{col 71}{space 3}-.0125388
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0567762{col 30}{space 2} .0185974{col 41}{space 1}   -3.05{col 50}{space 3}0.002{col 58}{space 4}-.0932265{col 71}{space 3}-.0203259
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0547846{col 30}{space 2} .0260188{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4}-.1057805{col 71}{space 3}-.0037886
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0310166{col 30}{space 2} .0242491{col 41}{space 1}    1.28{col 50}{space 3}0.201{col 58}{space 4}-.0165108{col 71}{space 3}  .078544
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} -.027869{col 30}{space 2} .0377098{col 41}{space 1}   -0.74{col 50}{space 3}0.460{col 58}{space 4}-.1017789{col 71}{space 3} .0460408
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0051149{col 30}{space 2} .0409554{col 41}{space 1}    0.12{col 50}{space 3}0.901{col 58}{space 4}-.0751562{col 71}{space 3}  .085386
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0132904{col 30}{space 2} .0285995{col 41}{space 1}    0.46{col 50}{space 3}0.642{col 58}{space 4}-.0427636{col 71}{space 3} .0693444
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .1132121{col 30}{space 2} .0286855{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} .0569896{col 71}{space 3} .1694347
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0107862{col 30}{space 2} .0032259{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4} .0044635{col 71}{space 3}  .017109
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .153217{col 30}{space 2} .0379171{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .0789009{col 71}{space 3} .2275332
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2751525{col 30}{space 2} .0355251{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .2055246{col 71}{space 3} .3447805
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} -.003778{col 30}{space 2} .0358109{col 41}{space 1}   -0.11{col 50}{space 3}0.916{col 58}{space 4}-.0739662{col 71}{space 3} .0664101
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3268464{col 30}{space 2} .0447814{col 41}{space 1}   -7.30{col 50}{space 3}0.000{col 58}{space 4}-.4146163{col 71}{space 3}-.2390765
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.2906947{col 30}{space 2} .0542619{col 41}{space 1}   -5.36{col 50}{space 3}0.000{col 58}{space 4} -.397046{col 71}{space 3}-.1843434
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2018485{col 30}{space 2} .0356193{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.2716611{col 71}{space 3} -.132036
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2424594{col 30}{space 2} .0138846{col 41}{space 1}   17.46{col 50}{space 3}0.000{col 58}{space 4}  .215246{col 71}{space 3} .2696728
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5127489{col 30}{space 2} .0230625{col 41}{space 1}  -22.23{col 50}{space 3}0.000{col 58}{space 4}-.5579505{col 71}{space 3}-.4675473
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.260233{col 30}{space 2} .0206785{col 41}{space 1}  -12.58{col 50}{space 3}0.000{col 58}{space 4}-.3007621{col 71}{space 3}-.2197038
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} -.273339{col 30}{space 2} .0213185{col 41}{space 1}  -12.82{col 50}{space 3}0.000{col 58}{space 4}-.3151225{col 71}{space 3}-.2315554
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23070.208}  
Iteration 1:{space 3}log pseudolikelihood = {res:-23063.773}  
Iteration 2:{space 3}log pseudolikelihood = {res:-23063.748}  
Iteration 3:{space 3}log pseudolikelihood = {res:-23063.748}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    17,046
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}  11848.19
{txt}Log pseudolikelihood = {res}-23063.748{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1659281{col 30}{space 2} .0068173{col 41}{space 1}   24.34{col 50}{space 3}0.000{col 58}{space 4} .1525665{col 71}{space 3} .1792897
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0039674{col 30}{space 2} .0024533{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0008411{col 71}{space 3} .0087758
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0718387{col 30}{space 2} .0295422{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4}  .013937{col 71}{space 3} .1297404
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006912{col 30}{space 2} .0004665{col 41}{space 1}   -1.48{col 50}{space 3}0.138{col 58}{space 4}-.0016054{col 71}{space 3} .0002231
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0453365{col 30}{space 2} .0170618{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4} -.078777{col 71}{space 3} -.011896
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0067445{col 30}{space 2} .0153706{col 41}{space 1}   -0.44{col 50}{space 3}0.661{col 58}{space 4}-.0368703{col 71}{space 3} .0233813
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0702612{col 30}{space 2} .0362602{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0008075{col 71}{space 3} .1413299
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0273232{col 30}{space 2} .0182788{col 41}{space 1}   -1.49{col 50}{space 3}0.135{col 58}{space 4}-.0631489{col 71}{space 3} .0085025
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.1235359{col 30}{space 2} .0304003{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.1831194{col 71}{space 3}-.0639525
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0188509{col 30}{space 2}   .01515{col 41}{space 1}   -1.24{col 50}{space 3}0.213{col 58}{space 4}-.0485444{col 71}{space 3} .0108425
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0102708{col 30}{space 2} .0159273{col 41}{space 1}    0.64{col 50}{space 3}0.519{col 58}{space 4}-.0209462{col 71}{space 3} .0414878
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0194278{col 30}{space 2}  .015235{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0492879{col 71}{space 3} .0104323
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0030677{col 30}{space 2} .0010947{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0009221{col 71}{space 3} .0052133
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0879548{col 30}{space 2} .0137272{col 41}{space 1}    6.41{col 50}{space 3}0.000{col 58}{space 4} .0610499{col 71}{space 3} .1148598
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0712183{col 30}{space 2} .0495718{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4}-.0259406{col 71}{space 3} .1683771
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1158498{col 30}{space 2} .0256695{col 41}{space 1}   -4.51{col 50}{space 3}0.000{col 58}{space 4} -.166161{col 71}{space 3}-.0655385
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1938953{col 30}{space 2} .0406248{col 41}{space 1}   -4.77{col 50}{space 3}0.000{col 58}{space 4}-.2735185{col 71}{space 3}-.1142721
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1155659{col 30}{space 2} .0232957{col 41}{space 1}   -4.96{col 50}{space 3}0.000{col 58}{space 4}-.1612246{col 71}{space 3}-.0699072
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1609226{col 30}{space 2} .0238769{col 41}{space 1}   -6.74{col 50}{space 3}0.000{col 58}{space 4}-.2077204{col 71}{space 3}-.1141248
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .1991994{col 30}{space 2}  .007967{col 41}{space 1}   25.00{col 50}{space 3}0.000{col 58}{space 4} .1835844{col 71}{space 3} .2148143
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0042768{col 30}{space 2} .0144687{col 41}{space 1}    0.30{col 50}{space 3}0.768{col 58}{space 4}-.0240814{col 71}{space 3}  .032635
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0034963{col 30}{space 2} .0126283{col 41}{space 1}   -0.28{col 50}{space 3}0.782{col 58}{space 4}-.0282473{col 71}{space 3} .0212547
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0462591{col 30}{space 2} .0164883{col 41}{space 1}   -2.81{col 50}{space 3}0.005{col 58}{space 4}-.0785755{col 71}{space 3}-.0139426
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.4791533{col 30}{space 2} .0381284{col 41}{space 1}  -12.57{col 50}{space 3}0.000{col 58}{space 4}-.5538835{col 71}{space 3} -.404423
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    17,046
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2806254{col 30}{space 2} .0115246{col 41}{space 1}   24.35{col 50}{space 3}0.000{col 58}{space 4} .2580376{col 71}{space 3} .3032132
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0067098{col 30}{space 2}   .00415{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4} -.001424{col 71}{space 3} .0148436
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .121497{col 30}{space 2} .0499483{col 41}{space 1}    2.43{col 50}{space 3}0.015{col 58}{space 4} .0236002{col 71}{space 3} .2193938
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011689{col 30}{space 2} .0007885{col 41}{space 1}   -1.48{col 50}{space 3}0.138{col 58}{space 4}-.0027144{col 71}{space 3} .0003766
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0766752{col 30}{space 2} .0288457{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4}-.1332117{col 71}{space 3}-.0201386
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}-.0114066{col 30}{space 2} .0259921{col 41}{space 1}   -0.44{col 50}{space 3}0.661{col 58}{space 4}-.0623501{col 71}{space 3}  .039537
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .118829{col 30}{space 2} .0613547{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0014239{col 71}{space 3}  .239082
{txt}{space 11}phone {c |}{col 18}{res}{space 2}-.0462103{col 30}{space 2} .0309099{col 41}{space 1}   -1.50{col 50}{space 3}0.135{col 58}{space 4}-.1067925{col 71}{space 3}  .014372
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.2089298{col 30}{space 2} .0514033{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.3096784{col 71}{space 3}-.1081812
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0318816{col 30}{space 2} .0256215{col 41}{space 1}   -1.24{col 50}{space 3}0.213{col 58}{space 4}-.0820988{col 71}{space 3} .0183356
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0173705{col 30}{space 2} .0269375{col 41}{space 1}    0.64{col 50}{space 3}0.519{col 58}{space 4} -.035426{col 71}{space 3}  .070167
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0328572{col 30}{space 2} .0257727{col 41}{space 1}   -1.27{col 50}{space 3}0.202{col 58}{space 4}-.0833707{col 71}{space 3} .0176564
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0051883{col 30}{space 2} .0018521{col 41}{space 1}    2.80{col 50}{space 3}0.005{col 58}{space 4} .0015583{col 71}{space 3} .0088183
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1487534{col 30}{space 2} .0233092{col 41}{space 1}    6.38{col 50}{space 3}0.000{col 58}{space 4} .1030681{col 71}{space 3} .1944387
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1204477{col 30}{space 2} .0838389{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4}-.0438736{col 71}{space 3}  .284769
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.1959306{col 30}{space 2} .0434298{col 41}{space 1}   -4.51{col 50}{space 3}0.000{col 58}{space 4}-.2810514{col 71}{space 3}-.1108098
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3279249{col 30}{space 2} .0686609{col 41}{space 1}   -4.78{col 50}{space 3}0.000{col 58}{space 4}-.4624978{col 71}{space 3} -.193352
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1954505{col 30}{space 2} .0394241{col 41}{space 1}   -4.96{col 50}{space 3}0.000{col 58}{space 4}-.2727203{col 71}{space 3}-.1181806
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.2721599{col 30}{space 2}   .04042{col 41}{space 1}   -6.73{col 50}{space 3}0.000{col 58}{space 4}-.3513818{col 71}{space 3}-.1929381
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .3368954{col 30}{space 2} .0138082{col 41}{space 1}   24.40{col 50}{space 3}0.000{col 58}{space 4} .3098317{col 71}{space 3}  .363959
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0072331{col 30}{space 2} .0244712{col 41}{space 1}    0.30{col 50}{space 3}0.768{col 58}{space 4}-.0407296{col 71}{space 3} .0551958
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0059131{col 30}{space 2} .0213594{col 41}{space 1}   -0.28{col 50}{space 3}0.782{col 58}{space 4}-.0477768{col 71}{space 3} .0359505
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0782355{col 30}{space 2} .0279617{col 41}{space 1}   -2.80{col 50}{space 3}0.005{col 58}{space 4}-.1330395{col 71}{space 3}-.0234315
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9_own  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-33539.396}  
Iteration 1:{space 3}log pseudolikelihood = {res:-33537.052}  
Iteration 2:{space 3}log pseudolikelihood = {res:-33537.052}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    20,293
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   6169.23
{txt}Log pseudolikelihood = {res}-33537.052{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}        hdd9_own{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0924864{col 30}{space 2} .0045901{col 41}{space 1}   20.15{col 50}{space 3}0.000{col 58}{space 4} .0834899{col 71}{space 3} .1014828
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0067922{col 30}{space 2} .0019224{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0030243{col 71}{space 3} .0105601
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0428316{col 30}{space 2} .0224427{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0011552{col 71}{space 3} .0868184
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005934{col 30}{space 2} .0003627{col 41}{space 1}    1.64{col 50}{space 3}0.102{col 58}{space 4}-.0001175{col 71}{space 3} .0013043
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0043948{col 30}{space 2} .0124193{col 41}{space 1}    0.35{col 50}{space 3}0.723{col 58}{space 4}-.0199465{col 71}{space 3} .0287361
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0557407{col 30}{space 2} .0121912{col 41}{space 1}    4.57{col 50}{space 3}0.000{col 58}{space 4} .0318465{col 71}{space 3}  .079635
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0051121{col 30}{space 2} .0183406{col 41}{space 1}    0.28{col 50}{space 3}0.780{col 58}{space 4}-.0308349{col 71}{space 3} .0410591
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0383626{col 30}{space 2} .0118988{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0150414{col 71}{space 3} .0616838
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0144119{col 30}{space 2} .0121983{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0094963{col 71}{space 3} .0383201
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0659978{col 30}{space 2} .0102847{col 41}{space 1}   -6.42{col 50}{space 3}0.000{col 58}{space 4}-.0861555{col 71}{space 3}-.0458401
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0067589{col 30}{space 2} .0110408{col 41}{space 1}   -0.61{col 50}{space 3}0.540{col 58}{space 4}-.0283986{col 71}{space 3} .0148807
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0001841{col 30}{space 2} .0091468{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.0181115{col 71}{space 3} .0177432
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0016973{col 30}{space 2} .0006208{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4} .0004806{col 71}{space 3}  .002914
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0793942{col 30}{space 2}  .010033{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4}   .05973{col 71}{space 3} .0990585
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0463127{col 30}{space 2} .0314517{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0153314{col 71}{space 3} .1079568
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0292176{col 30}{space 2}  .021922{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.0721839{col 71}{space 3} .0137487
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.1605511{col 30}{space 2} .0253508{col 41}{space 1}   -6.33{col 50}{space 3}0.000{col 58}{space 4}-.2102377{col 71}{space 3}-.1108644
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0776494{col 30}{space 2} .0199513{col 41}{space 1}   -3.89{col 50}{space 3}0.000{col 58}{space 4}-.1167533{col 71}{space 3}-.0385455
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1490236{col 30}{space 2} .0194089{col 41}{space 1}   -7.68{col 50}{space 3}0.000{col 58}{space 4}-.1870644{col 71}{space 3}-.1109828
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .2646319{col 30}{space 2} .0072767{col 41}{space 1}   36.37{col 50}{space 3}0.000{col 58}{space 4} .2503698{col 71}{space 3}  .278894
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0671542{col 30}{space 2} .0128915{col 41}{space 1}   -5.21{col 50}{space 3}0.000{col 58}{space 4} -.092421{col 71}{space 3}-.0418874
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0248961{col 30}{space 2} .0121762{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0010311{col 71}{space 3}  .048761
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1450837{col 30}{space 2} .0112924{col 41}{space 1}   12.85{col 50}{space 3}0.000{col 58}{space 4}  .122951{col 71}{space 3} .1672164
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0975705{col 30}{space 2}   .01134{col 41}{space 1}    8.60{col 50}{space 3}0.000{col 58}{space 4} .0753446{col 71}{space 3} .1197965
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .1516539{col 30}{space 2} .0108356{col 41}{space 1}   14.00{col 50}{space 3}0.000{col 58}{space 4} .1304165{col 71}{space 3} .1728913
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}-.3712357{col 30}{space 2} .0337258{col 41}{space 1}  -11.01{col 50}{space 3}0.000{col 58}{space 4}-.4373371{col 71}{space 3}-.3051344
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    20,293
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2292858{col 30}{space 2} .0113799{col 41}{space 1}   20.15{col 50}{space 3}0.000{col 58}{space 4} .2069815{col 71}{space 3} .2515901
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0168387{col 30}{space 2} .0047708{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0074881{col 71}{space 3} .0261892
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1061852{col 30}{space 2} .0555994{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0027877{col 71}{space 3} .2151581
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0014711{col 30}{space 2} .0008995{col 41}{space 1}    1.64{col 50}{space 3}0.102{col 58}{space 4}-.0002919{col 71}{space 3} .0032341
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0108952{col 30}{space 2} .0307883{col 41}{space 1}    0.35{col 50}{space 3}0.723{col 58}{space 4}-.0494486{col 71}{space 3} .0712391
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1381886{col 30}{space 2} .0302086{col 41}{space 1}    4.57{col 50}{space 3}0.000{col 58}{space 4} .0789807{col 71}{space 3} .1973964
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0126736{col 30}{space 2} .0454698{col 41}{space 1}    0.28{col 50}{space 3}0.780{col 58}{space 4}-.0764456{col 71}{space 3} .1017928
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .095106{col 30}{space 2} .0294928{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0373011{col 71}{space 3} .1529108
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0357289{col 30}{space 2} .0302499{col 41}{space 1}    1.18{col 50}{space 3}0.238{col 58}{space 4}-.0235598{col 71}{space 3} .0950175
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.1636171{col 30}{space 2} .0254856{col 41}{space 1}   -6.42{col 50}{space 3}0.000{col 58}{space 4} -.213568{col 71}{space 3}-.1136662
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0167563{col 30}{space 2} .0273714{col 41}{space 1}   -0.61{col 50}{space 3}0.540{col 58}{space 4}-.0704031{col 71}{space 3} .0368906
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0004565{col 30}{space 2}  .022676{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.0449007{col 71}{space 3} .0439877
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0042079{col 30}{space 2} .0015387{col 41}{space 1}    2.73{col 50}{space 3}0.006{col 58}{space 4}  .001192{col 71}{space 3} .0072237
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1968286{col 30}{space 2} .0249293{col 41}{space 1}    7.90{col 50}{space 3}0.000{col 58}{space 4} .1479682{col 71}{space 3} .2456891
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1148153{col 30}{space 2} .0779866{col 41}{space 1}    1.47{col 50}{space 3}0.141{col 58}{space 4}-.0380356{col 71}{space 3} .2676661
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}-.0724342{col 30}{space 2} .0543499{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.1789581{col 71}{space 3} .0340896
{txt}electricity_mean {c |}{col 18}{res}{space 2}-.3980271{col 30}{space 2} .0628348{col 41}{space 1}   -6.33{col 50}{space 3}0.000{col 58}{space 4} -.521181{col 71}{space 3}-.2748731
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.1925031{col 30}{space 2} .0494811{col 41}{space 1}   -3.89{col 50}{space 3}0.000{col 58}{space 4}-.2894842{col 71}{space 3}-.0955219
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} -.369449{col 30}{space 2} .0480858{col 41}{space 1}   -7.68{col 50}{space 3}0.000{col 58}{space 4}-.4636955{col 71}{space 3}-.2752024
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .656057{col 30}{space 2} .0182068{col 41}{space 1}   36.03{col 50}{space 3}0.000{col 58}{space 4} .6203723{col 71}{space 3} .6917417
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.166484{col 30}{space 2} .0319405{col 41}{space 1}   -5.21{col 50}{space 3}0.000{col 58}{space 4}-.2290864{col 71}{space 3}-.1038817
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0617206{col 30}{space 2} .0301866{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0025561{col 71}{space 3} .1208852
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3596815{col 30}{space 2} .0281047{col 41}{space 1}   12.80{col 50}{space 3}0.000{col 58}{space 4} .3045973{col 71}{space 3} .4147657
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}   .24189{col 30}{space 2} .0281475{col 41}{space 1}    8.59{col 50}{space 3}0.000{col 58}{space 4}  .186722{col 71}{space 3} .2970581
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3759698{col 30}{space 2}  .026859{col 41}{space 1}   14.00{col 50}{space 3}0.000{col 58}{space 4} .3233272{col 71}{space 3} .4286124
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S22_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean  )
{res}{txt}(note: file S22_poisson.rtf not found)
(output written to {browse  `"S22_poisson.rtf"'})

{com}. 
. 
. 
. 
. ********************************************************************************
. *                                   S23                                        *
. ********************************************************************************
. eststo clear
{txt}
{com}. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-164658.54}  
Iteration 1:{space 3}log pseudolikelihood = {res:-164658.41}  
Iteration 2:{space 3}log pseudolikelihood = {res:-164658.41}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    82,550
{txt}{col 49}Wald chi2({res}35{txt}){col 67}= {res}  35602.64
{txt}Log pseudolikelihood = {res}-164658.41{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:34,744} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0029032{col 30}{space 2} .0015577{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.0001497{col 71}{space 3} .0059562
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.000912{col 30}{space 2} .0006791{col 41}{space 1}   -1.34{col 50}{space 3}0.179{col 58}{space 4} -.002243{col 71}{space 3}  .000419
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0151915{col 30}{space 2} .0072031{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4}-.0293093{col 71}{space 3}-.0010737
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0010217{col 30}{space 2} .0001267{col 41}{space 1}   -8.06{col 50}{space 3}0.000{col 58}{space 4}-.0012701{col 71}{space 3}-.0007734
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0178008{col 30}{space 2} .0042779{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0094162{col 71}{space 3} .0261854
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0836315{col 30}{space 2} .0041866{col 41}{space 1}   19.98{col 50}{space 3}0.000{col 58}{space 4}  .075426{col 71}{space 3}  .091837
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0234727{col 30}{space 2} .0057087{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0122838{col 71}{space 3} .0346616
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0712613{col 30}{space 2} .0051175{col 41}{space 1}   13.93{col 50}{space 3}0.000{col 58}{space 4} .0612312{col 71}{space 3} .0812914
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0608703{col 30}{space 2}  .005259{col 41}{space 1}   11.57{col 50}{space 3}0.000{col 58}{space 4}  .050563{col 71}{space 3} .0711777
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}   .04918{col 30}{space 2}  .004307{col 41}{space 1}   11.42{col 50}{space 3}0.000{col 58}{space 4} .0407385{col 71}{space 3} .0576216
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0665627{col 30}{space 2} .0042738{col 41}{space 1}   15.57{col 50}{space 3}0.000{col 58}{space 4} .0581862{col 71}{space 3} .0749391
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0271883{col 30}{space 2} .0040549{col 41}{space 1}   -6.70{col 50}{space 3}0.000{col 58}{space 4}-.0351359{col 71}{space 3}-.0192408
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004102{col 30}{space 2} .0003736{col 41}{space 1}   -1.10{col 50}{space 3}0.272{col 58}{space 4}-.0011424{col 71}{space 3}  .000322
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0336058{col 30}{space 2}  .005523{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4}-.0444307{col 71}{space 3}-.0227809
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .008191{col 30}{space 2}   .00786{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0072143{col 71}{space 3} .0235963
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1803809{col 30}{space 2} .0077219{col 41}{space 1}   23.36{col 50}{space 3}0.000{col 58}{space 4} .1652464{col 71}{space 3} .1955155
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1371387{col 30}{space 2} .0071337{col 41}{space 1}   19.22{col 50}{space 3}0.000{col 58}{space 4}  .123157{col 71}{space 3} .1511205
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0651086{col 30}{space 2} .0063694{col 41}{space 1}   10.22{col 50}{space 3}0.000{col 58}{space 4} .0526248{col 71}{space 3} .0775924
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1065758{col 30}{space 2} .0061066{col 41}{space 1}   17.45{col 50}{space 3}0.000{col 58}{space 4} .0946071{col 71}{space 3} .1185445
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0560161{col 30}{space 2} .0020076{col 41}{space 1}  -27.90{col 50}{space 3}0.000{col 58}{space 4} -.059951{col 71}{space 3}-.0520812
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.183891{col 30}{space 2} .0075724{col 41}{space 1}  -24.28{col 50}{space 3}0.000{col 58}{space 4}-.1987327{col 71}{space 3}-.1690493
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.5041075{col 30}{space 2} .0089241{col 41}{space 1}  -56.49{col 50}{space 3}0.000{col 58}{space 4}-.5215985{col 71}{space 3}-.4866165
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.3114143{col 30}{space 2} .0082014{col 41}{space 1}  -37.97{col 50}{space 3}0.000{col 58}{space 4}-.3274887{col 71}{space 3}-.2953399
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.2060198{col 30}{space 2}   .00719{col 41}{space 1}  -28.65{col 50}{space 3}0.000{col 58}{space 4}-.2201119{col 71}{space 3}-.1919277
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}-.0584745{col 30}{space 2} .0091034{col 41}{space 1}   -6.42{col 50}{space 3}0.000{col 58}{space 4}-.0763169{col 71}{space 3}-.0406322
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0578298{col 30}{space 2} .0112127{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0798063{col 71}{space 3}-.0358533
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} -.007667{col 30}{space 2} .0071064{col 41}{space 1}   -1.08{col 50}{space 3}0.281{col 58}{space 4}-.0215953{col 71}{space 3} .0062613
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0549885{col 30}{space 2} .0087391{col 41}{space 1}   -6.29{col 50}{space 3}0.000{col 58}{space 4}-.0721168{col 71}{space 3}-.0378602
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0144241{col 30}{space 2} .0071891{col 41}{space 1}   -2.01{col 50}{space 3}0.045{col 58}{space 4}-.0285144{col 71}{space 3}-.0003338
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0151921{col 30}{space 2} .0086297{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0017217{col 71}{space 3} .0321059
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.036032{col 30}{space 2} .0083184{col 41}{space 1}   -4.33{col 50}{space 3}0.000{col 58}{space 4}-.0523357{col 71}{space 3}-.0197283
{txt}{space 11}2015  {c |}{col 18}{res}{space 2}  .040456{col 30}{space 2}  .007951{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .0248723{col 71}{space 3} .0560396
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .0195291{col 30}{space 2} .0106901{col 41}{space 1}    1.83{col 50}{space 3}0.068{col 58}{space 4}-.0014232{col 71}{space 3} .0404814
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0454364{col 30}{space 2} .0084117{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .0289497{col 71}{space 3} .0619231
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0183227{col 30}{space 2} .0087583{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0011568{col 71}{space 3} .0354886
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.475556{col 30}{space 2}  .012623{col 41}{space 1}  116.89{col 50}{space 3}0.000{col 58}{space 4} 1.450815{col 71}{space 3} 1.500296
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    82,550
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0130705{col 30}{space 2} .0070126{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4} -.000674{col 71}{space 3}  .026815
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0041058{col 30}{space 2} .0030576{col 41}{space 1}   -1.34{col 50}{space 3}0.179{col 58}{space 4}-.0100986{col 71}{space 3} .0018869
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.068393{col 30}{space 2} .0324268{col 41}{space 1}   -2.11{col 50}{space 3}0.035{col 58}{space 4}-.1319484{col 71}{space 3}-.0048375
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}   -.0046{col 30}{space 2} .0005699{col 41}{space 1}   -8.07{col 50}{space 3}0.000{col 58}{space 4} -.005717{col 71}{space 3}-.0034829
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}   .08014{col 30}{space 2} .0192614{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0423883{col 71}{space 3} .1178916
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .376513{col 30}{space 2} .0188516{col 41}{space 1}   19.97{col 50}{space 3}0.000{col 58}{space 4} .3395644{col 71}{space 3} .4134615
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1056752{col 30}{space 2} .0257014{col 41}{space 1}    4.11{col 50}{space 3}0.000{col 58}{space 4} .0553013{col 71}{space 3} .1560491
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3208217{col 30}{space 2} .0230373{col 41}{space 1}   13.93{col 50}{space 3}0.000{col 58}{space 4} .2756695{col 71}{space 3} .3659739
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .274041{col 30}{space 2} .0236702{col 41}{space 1}   11.58{col 50}{space 3}0.000{col 58}{space 4} .2276482{col 71}{space 3} .3204338
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2214108{col 30}{space 2} .0193912{col 41}{space 1}   11.42{col 50}{space 3}0.000{col 58}{space 4} .1834047{col 71}{space 3} .2594169
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2996683{col 30}{space 2} .0192398{col 41}{space 1}   15.58{col 50}{space 3}0.000{col 58}{space 4} .2619591{col 71}{space 3} .3373776
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.122403{col 30}{space 2} .0182628{col 41}{space 1}   -6.70{col 50}{space 3}0.000{col 58}{space 4}-.1581975{col 71}{space 3}-.0866086
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0018467{col 30}{space 2} .0016817{col 41}{space 1}   -1.10{col 50}{space 3}0.272{col 58}{space 4}-.0051428{col 71}{space 3} .0014494
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1512949{col 30}{space 2} .0248608{col 41}{space 1}   -6.09{col 50}{space 3}0.000{col 58}{space 4}-.2000212{col 71}{space 3}-.1025686
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0368762{col 30}{space 2} .0353863{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0324797{col 71}{space 3} .1062321
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8120835{col 30}{space 2} .0347271{col 41}{space 1}   23.38{col 50}{space 3}0.000{col 58}{space 4} .7440196{col 71}{space 3} .8801474
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6174051{col 30}{space 2} .0321011{col 41}{space 1}   19.23{col 50}{space 3}0.000{col 58}{space 4} .5544882{col 71}{space 3}  .680322
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .293122{col 30}{space 2} .0286745{col 41}{space 1}   10.22{col 50}{space 3}0.000{col 58}{space 4}  .236921{col 71}{space 3} .3493229
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4798094{col 30}{space 2} .0274701{col 41}{space 1}   17.47{col 50}{space 3}0.000{col 58}{space 4} .4259691{col 71}{space 3} .5336498
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2521873{col 30}{space 2} .0090217{col 41}{space 1}  -27.95{col 50}{space 3}0.000{col 58}{space 4}-.2698695{col 71}{space 3}-.2345051
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.941697{col 30}{space 2} .0404963{col 41}{space 1}  -23.25{col 50}{space 3}0.000{col 58}{space 4}-1.021068{col 71}{space 3}-.8623257
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-2.219815{col 30}{space 2} .0412844{col 41}{space 1}  -53.77{col 50}{space 3}0.000{col 58}{space 4}-2.300731{col 71}{space 3}  -2.1389
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-1.500167{col 30}{space 2} .0416303{col 41}{space 1}  -36.04{col 50}{space 3}0.000{col 58}{space 4}-1.581761{col 71}{space 3}-1.418573
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-1.043784{col 30}{space 2} .0382516{col 41}{space 1}  -27.29{col 50}{space 3}0.000{col 58}{space 4}-1.118756{col 71}{space 3}-.9688121
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}-.3184208{col 30}{space 2} .0496786{col 41}{space 1}   -6.41{col 50}{space 3}0.000{col 58}{space 4}-.4157891{col 71}{space 3}-.2210525
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2530471{col 30}{space 2} .0487887{col 41}{space 1}   -5.19{col 50}{space 3}0.000{col 58}{space 4}-.3486712{col 71}{space 3}-.1574229
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} -.034396{col 30}{space 2} .0319726{col 41}{space 1}   -1.08{col 50}{space 3}0.282{col 58}{space 4}-.0970611{col 71}{space 3} .0282691
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.2409533{col 30}{space 2} .0386381{col 41}{space 1}   -6.24{col 50}{space 3}0.000{col 58}{space 4}-.3166826{col 71}{space 3} -.165224
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0644921{col 30}{space 2} .0323009{col 41}{space 1}   -2.00{col 50}{space 3}0.046{col 58}{space 4}-.1278006{col 71}{space 3}-.0011836
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0689395{col 30}{space 2} .0390489{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4} -.007595{col 71}{space 3}  .145474
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1593802{col 30}{space 2} .0370368{col 41}{space 1}   -4.30{col 50}{space 3}0.000{col 58}{space 4} -.231971{col 71}{space 3}-.0867894
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1859276{col 30}{space 2} .0361222{col 41}{space 1}    5.15{col 50}{space 3}0.000{col 58}{space 4} .1151294{col 71}{space 3} .2567257
{txt}{space 11}2016  {c |}{col 18}{res}{space 2} .0888131{col 30}{space 2} .0486632{col 41}{space 1}    1.83{col 50}{space 3}0.068{col 58}{space 4} -.006565{col 71}{space 3} .1841912
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .2093411{col 30}{space 2} .0384022{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .1340742{col 71}{space 3}  .284608
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} .0832762{col 30}{space 2} .0396884{col 41}{space 1}    2.10{col 50}{space 3}0.036{col 58}{space 4} .0054884{col 71}{space 3}  .161064
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-18794.639}  
Iteration 1:{space 3}log pseudolikelihood = {res:-18794.604}  
Iteration 2:{space 3}log pseudolikelihood = {res:-18794.604}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    10,583
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   6729.66
{txt}Log pseudolikelihood = {res}-18794.604{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,088} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0078815{col 30}{space 2} .0051758{col 41}{space 1}    1.52{col 50}{space 3}0.128{col 58}{space 4}-.0022629{col 71}{space 3} .0180259
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .012169{col 30}{space 2} .0027734{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .0067332{col 71}{space 3} .0176049
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .013041{col 30}{space 2} .0228441{col 41}{space 1}    0.57{col 50}{space 3}0.568{col 58}{space 4}-.0317326{col 71}{space 3} .0578147
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0023859{col 30}{space 2} .0003972{col 41}{space 1}   -6.01{col 50}{space 3}0.000{col 58}{space 4}-.0031645{col 71}{space 3}-.0016074
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0146171{col 30}{space 2} .0123081{col 41}{space 1}    1.19{col 50}{space 3}0.235{col 58}{space 4}-.0095063{col 71}{space 3} .0387405
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1086628{col 30}{space 2} .0128244{col 41}{space 1}    8.47{col 50}{space 3}0.000{col 58}{space 4} .0835275{col 71}{space 3} .1337981
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0115336{col 30}{space 2} .0449192{col 41}{space 1}    0.26{col 50}{space 3}0.797{col 58}{space 4}-.0765064{col 71}{space 3} .0995736
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0776072{col 30}{space 2} .0168459{col 41}{space 1}    4.61{col 50}{space 3}0.000{col 58}{space 4} .0445899{col 71}{space 3} .1106245
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1539753{col 30}{space 2} .0191377{col 41}{space 1}    8.05{col 50}{space 3}0.000{col 58}{space 4} .1164661{col 71}{space 3} .1914845
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0125945{col 30}{space 2} .0158175{col 41}{space 1}   -0.80{col 50}{space 3}0.426{col 58}{space 4}-.0435962{col 71}{space 3} .0184072
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0964711{col 30}{space 2} .0194472{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0583552{col 71}{space 3}  .134587
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0995922{col 30}{space 2} .0152605{col 41}{space 1}   -6.53{col 50}{space 3}0.000{col 58}{space 4}-.1295023{col 71}{space 3}-.0696822
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0046511{col 30}{space 2} .0031441{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.0108134{col 71}{space 3} .0015111
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1332129{col 30}{space 2} .0152173{col 41}{space 1}    8.75{col 50}{space 3}0.000{col 58}{space 4} .1033876{col 71}{space 3} .1630383
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1020917{col 30}{space 2} .0575176{col 41}{space 1}    1.77{col 50}{space 3}0.076{col 58}{space 4}-.0106408{col 71}{space 3} .2148242
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .2283867{col 30}{space 2} .0245175{col 41}{space 1}    9.32{col 50}{space 3}0.000{col 58}{space 4} .1803332{col 71}{space 3} .2764402
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2196315{col 30}{space 2}  .027057{col 41}{space 1}    8.12{col 50}{space 3}0.000{col 58}{space 4} .1666007{col 71}{space 3} .2726622
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1768926{col 30}{space 2} .0223629{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .1330621{col 71}{space 3} .2207231
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0989612{col 30}{space 2} .0234234{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .0530522{col 71}{space 3} .1448702
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0657144{col 30}{space 2} .0064722{col 41}{space 1}  -10.15{col 50}{space 3}0.000{col 58}{space 4}-.0783996{col 71}{space 3}-.0530292
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0757738{col 30}{space 2} .0082644{col 41}{space 1}   -9.17{col 50}{space 3}0.000{col 58}{space 4}-.0919718{col 71}{space 3}-.0595758
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .8116504{col 30}{space 2} .0295467{col 41}{space 1}   27.47{col 50}{space 3}0.000{col 58}{space 4} .7537399{col 71}{space 3} .8695609
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    10,583
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0242387{col 30}{space 2} .0159144{col 41}{space 1}    1.52{col 50}{space 3}0.128{col 58}{space 4} -.006953{col 71}{space 3} .0554304
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0374247{col 30}{space 2} .0085202{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .0207254{col 71}{space 3} .0541241
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0401065{col 30}{space 2} .0702549{col 41}{space 1}    0.57{col 50}{space 3}0.568{col 58}{space 4}-.0975906{col 71}{space 3} .1778035
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0073377{col 30}{space 2} .0012214{col 41}{space 1}   -6.01{col 50}{space 3}0.000{col 58}{space 4}-.0097315{col 71}{space 3}-.0049439
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0449536{col 30}{space 2} .0378476{col 41}{space 1}    1.19{col 50}{space 3}0.235{col 58}{space 4}-.0292264{col 71}{space 3} .1191336
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3341821{col 30}{space 2} .0394796{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .2568035{col 71}{space 3} .4115607
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0354704{col 30}{space 2} .1381455{col 41}{space 1}    0.26{col 50}{space 3}0.797{col 58}{space 4}-.2352897{col 71}{space 3} .3062306
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2386734{col 30}{space 2} .0518148{col 41}{space 1}    4.61{col 50}{space 3}0.000{col 58}{space 4} .1371183{col 71}{space 3} .3402285
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4735363{col 30}{space 2} .0588708{col 41}{space 1}    8.04{col 50}{space 3}0.000{col 58}{space 4} .3581516{col 71}{space 3} .5889209
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}-.0387332{col 30}{space 2} .0486479{col 41}{space 1}   -0.80{col 50}{space 3}0.426{col 58}{space 4}-.1340812{col 71}{space 3} .0566149
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2966876{col 30}{space 2} .0598077{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .1794666{col 71}{space 3} .4139085
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.3062864{col 30}{space 2} .0469792{col 41}{space 1}   -6.52{col 50}{space 3}0.000{col 58}{space 4}-.3983639{col 71}{space 3}-.2142089
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0143041{col 30}{space 2} .0096676{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-.0332521{col 71}{space 3}  .004644
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .4096835{col 30}{space 2}  .046968{col 41}{space 1}    8.72{col 50}{space 3}0.000{col 58}{space 4}  .317628{col 71}{space 3} .5017391
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .3139731{col 30}{space 2} .1768813{col 41}{space 1}    1.78{col 50}{space 3}0.076{col 58}{space 4}-.0327078{col 71}{space 3}  .660654
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7023815{col 30}{space 2} .0752947{col 41}{space 1}    9.33{col 50}{space 3}0.000{col 58}{space 4} .5548065{col 71}{space 3} .8499564
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6754554{col 30}{space 2} .0831298{col 41}{space 1}    8.13{col 50}{space 3}0.000{col 58}{space 4}  .512524{col 71}{space 3} .8383869
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5440161{col 30}{space 2} .0686692{col 41}{space 1}    7.92{col 50}{space 3}0.000{col 58}{space 4}  .409427{col 71}{space 3} .6786053
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3043456{col 30}{space 2} .0720283{col 41}{space 1}    4.23{col 50}{space 3}0.000{col 58}{space 4} .1631727{col 71}{space 3} .4455185
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2020983{col 30}{space 2} .0198865{col 41}{space 1}  -10.16{col 50}{space 3}0.000{col 58}{space 4}-.2410752{col 71}{space 3}-.1631215
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} -.233035{col 30}{space 2} .0253512{col 41}{space 1}   -9.19{col 50}{space 3}0.000{col 58}{space 4}-.2827224{col 71}{space 3}-.1833476
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-18631.951}  
Iteration 1:{space 3}log pseudolikelihood = {res:-18631.932}  
Iteration 2:{space 3}log pseudolikelihood = {res:-18631.932}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     9,155
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   5100.86
{txt}Log pseudolikelihood = {res}-18631.932{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,447} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0019173{col 30}{space 2} .0035701{col 41}{space 1}   -0.54{col 50}{space 3}0.591{col 58}{space 4}-.0089146{col 71}{space 3}   .00508
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0041376{col 30}{space 2} .0022827{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0003363{col 71}{space 3} .0086115
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1041479{col 30}{space 2} .0193688{col 41}{space 1}   -5.38{col 50}{space 3}0.000{col 58}{space 4}  -.14211{col 71}{space 3}-.0661857
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0019233{col 30}{space 2} .0003725{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0026534{col 71}{space 3}-.0011933
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0263466{col 30}{space 2} .0114932{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.0488729{col 71}{space 3}-.0038202
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0929194{col 30}{space 2} .0133269{col 41}{space 1}    6.97{col 50}{space 3}0.000{col 58}{space 4} .0667992{col 71}{space 3} .1190396
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0290813{col 30}{space 2} .0245548{col 41}{space 1}    1.18{col 50}{space 3}0.236{col 58}{space 4}-.0190451{col 71}{space 3} .0772078
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0980691{col 30}{space 2} .0134972{col 41}{space 1}    7.27{col 50}{space 3}0.000{col 58}{space 4}  .071615{col 71}{space 3} .1245231
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0777648{col 30}{space 2} .0152684{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .0478394{col 71}{space 3} .1076903
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0608058{col 30}{space 2} .0124915{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .0363229{col 71}{space 3} .0852886
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .072271{col 30}{space 2} .0097179{col 41}{space 1}    7.44{col 50}{space 3}0.000{col 58}{space 4} .0532243{col 71}{space 3} .0913176
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0284916{col 30}{space 2} .0086511{col 41}{space 1}   -3.29{col 50}{space 3}0.001{col 58}{space 4}-.0454474{col 71}{space 3}-.0115357
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0011011{col 30}{space 2} .0064951{col 41}{space 1}    0.17{col 50}{space 3}0.865{col 58}{space 4}-.0116292{col 71}{space 3} .0138313
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0116963{col 30}{space 2} .0139995{col 41}{space 1}   -0.84{col 50}{space 3}0.403{col 58}{space 4}-.0391349{col 71}{space 3} .0157422
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0845403{col 30}{space 2} .0418864{col 41}{space 1}    2.02{col 50}{space 3}0.044{col 58}{space 4} .0024444{col 71}{space 3} .1666362
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1297767{col 30}{space 2} .0204596{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .0896765{col 71}{space 3} .1698768
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1106014{col 30}{space 2} .0205036{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0704151{col 71}{space 3} .1507878
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1042715{col 30}{space 2} .0176226{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0697317{col 71}{space 3} .1388112
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1416844{col 30}{space 2} .0163403{col 41}{space 1}    8.67{col 50}{space 3}0.000{col 58}{space 4}  .109658{col 71}{space 3} .1737109
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0468711{col 30}{space 2} .0051105{col 41}{space 1}   -9.17{col 50}{space 3}0.000{col 58}{space 4}-.0568876{col 71}{space 3}-.0368547
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0476031{col 30}{space 2} .0106296{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.0684368{col 71}{space 3}-.0267694
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0001705{col 30}{space 2} .0082564{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.0163527{col 71}{space 3} .0160117
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.457803{col 30}{space 2} .0240427{col 41}{space 1}   60.63{col 50}{space 3}0.000{col 58}{space 4} 1.410681{col 71}{space 3} 1.504926
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     9,155
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}-.0095782{col 30}{space 2} .0178337{col 41}{space 1}   -0.54{col 50}{space 3}0.591{col 58}{space 4}-.0445315{col 71}{space 3} .0253752
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}   .02067{col 30}{space 2} .0114009{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0016755{col 71}{space 3} .0430154
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.5202842{col 30}{space 2} .0968593{col 41}{space 1}   -5.37{col 50}{space 3}0.000{col 58}{space 4} -.710125{col 71}{space 3}-.3304434
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0096082{col 30}{space 2} .0018571{col 41}{space 1}   -5.17{col 50}{space 3}0.000{col 58}{space 4} -.013248{col 71}{space 3}-.0059683
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1316177{col 30}{space 2} .0573855{col 41}{space 1}   -2.29{col 50}{space 3}0.022{col 58}{space 4}-.2440912{col 71}{space 3}-.0191441
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4641911{col 30}{space 2} .0665283{col 41}{space 1}    6.98{col 50}{space 3}0.000{col 58}{space 4} .3337981{col 71}{space 3} .5945841
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1452797{col 30}{space 2} .1226708{col 41}{space 1}    1.18{col 50}{space 3}0.236{col 58}{space 4}-.0951506{col 71}{space 3}   .38571
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .4899168{col 30}{space 2} .0674529{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .3577116{col 71}{space 3}  .622122
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3884844{col 30}{space 2} .0762666{col 41}{space 1}    5.09{col 50}{space 3}0.000{col 58}{space 4} .2390046{col 71}{space 3} .5379643
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .3037632{col 30}{space 2} .0623903{col 41}{space 1}    4.87{col 50}{space 3}0.000{col 58}{space 4} .1814806{col 71}{space 3} .4260459
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3610391{col 30}{space 2} .0485245{col 41}{space 1}    7.44{col 50}{space 3}0.000{col 58}{space 4} .2659328{col 71}{space 3} .4561454
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1423333{col 30}{space 2}  .043228{col 41}{space 1}   -3.29{col 50}{space 3}0.001{col 58}{space 4}-.2270586{col 71}{space 3} -.057608
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0055006{col 30}{space 2} .0324471{col 41}{space 1}    0.17{col 50}{space 3}0.865{col 58}{space 4}-.0580946{col 71}{space 3} .0690957
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0584306{col 30}{space 2} .0699218{col 41}{space 1}   -0.84{col 50}{space 3}0.403{col 58}{space 4}-.1954749{col 71}{space 3} .0786137
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4223322{col 30}{space 2} .2091942{col 41}{space 1}    2.02{col 50}{space 3}0.044{col 58}{space 4} .0123191{col 71}{space 3} .8323453
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6483163{col 30}{space 2} .1022107{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .4479869{col 71}{space 3} .8486456
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5525239{col 30}{space 2} .1022505{col 41}{space 1}    5.40{col 50}{space 3}0.000{col 58}{space 4} .3521166{col 71}{space 3} .7529313
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .5209017{col 30}{space 2} .0880152{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .3483951{col 71}{space 3} .6934083
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7078032{col 30}{space 2} .0816316{col 41}{space 1}    8.67{col 50}{space 3}0.000{col 58}{space 4} .5478082{col 71}{space 3} .8677981
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2341509{col 30}{space 2} .0255254{col 41}{space 1}   -9.17{col 50}{space 3}0.000{col 58}{space 4}-.2841798{col 71}{space 3}-.1841221
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2378075{col 30}{space 2} .0530363{col 41}{space 1}   -4.48{col 50}{space 3}0.000{col 58}{space 4}-.3417567{col 71}{space 3}-.1338582
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0008517{col 30}{space 2} .0412455{col 41}{space 1}   -0.02{col 50}{space 3}0.984{col 58}{space 4}-.0816915{col 71}{space 3} .0799881
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -14345.57}  
Iteration 1:{space 3}log pseudolikelihood = {res: -14345.57}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     7,044
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   2238.73
{txt}Log pseudolikelihood = {res} -14345.57{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,069} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0448069{col 30}{space 2} .0074348{col 41}{space 1}    6.03{col 50}{space 3}0.000{col 58}{space 4}  .030235{col 71}{space 3} .0593787
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0035826{col 30}{space 2} .0013447{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0009471{col 71}{space 3} .0062181
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0175262{col 30}{space 2} .0206384{col 41}{space 1}   -0.85{col 50}{space 3}0.396{col 58}{space 4}-.0579767{col 71}{space 3} .0229244
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0001349{col 30}{space 2} .0003207{col 41}{space 1}    0.42{col 50}{space 3}0.674{col 58}{space 4}-.0004937{col 71}{space 3} .0007634
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0157892{col 30}{space 2}  .012268{col 41}{space 1}    1.29{col 50}{space 3}0.198{col 58}{space 4}-.0082557{col 71}{space 3} .0398341
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0707137{col 30}{space 2} .0089638{col 41}{space 1}    7.89{col 50}{space 3}0.000{col 58}{space 4}  .053145{col 71}{space 3} .0882825
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0385649{col 30}{space 2} .0168217{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0055951{col 71}{space 3} .0715348
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0305343{col 30}{space 2} .0163537{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0015185{col 71}{space 3}  .062587
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0388702{col 30}{space 2} .0186196{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0023765{col 71}{space 3} .0753639
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0506159{col 30}{space 2} .0160356{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .0191866{col 71}{space 3} .0820451
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0337634{col 30}{space 2} .0142777{col 41}{space 1}   -2.36{col 50}{space 3}0.018{col 58}{space 4}-.0617472{col 71}{space 3}-.0057795
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0347681{col 30}{space 2} .0106247{col 41}{space 1}   -3.27{col 50}{space 3}0.001{col 58}{space 4}-.0555922{col 71}{space 3}-.0139441
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0002644{col 30}{space 2} .0003508{col 41}{space 1}   -0.75{col 50}{space 3}0.451{col 58}{space 4}-.0009519{col 71}{space 3} .0004232
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0185019{col 30}{space 2} .0479534{col 41}{space 1}    0.39{col 50}{space 3}0.700{col 58}{space 4}-.0754851{col 71}{space 3} .1124889
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0208655{col 30}{space 2} .0211217{col 41}{space 1}    0.99{col 50}{space 3}0.323{col 58}{space 4}-.0205324{col 71}{space 3} .0622633
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0986967{col 30}{space 2} .0204813{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .0585542{col 71}{space 3} .1388392
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1071965{col 30}{space 2} .0222512{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .0635849{col 71}{space 3} .1508082
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0467141{col 30}{space 2} .0201837{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0071548{col 71}{space 3} .0862735
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1194543{col 30}{space 2} .0176158{col 41}{space 1}    6.78{col 50}{space 3}0.000{col 58}{space 4}  .084928{col 71}{space 3} .1539807
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0633356{col 30}{space 2} .0085652{col 41}{space 1}   -7.39{col 50}{space 3}0.000{col 58}{space 4}-.0801232{col 71}{space 3}-.0465481
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0032602{col 30}{space 2} .0075363{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0115106{col 71}{space 3} .0180311
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.446742{col 30}{space 2} .0235718{col 41}{space 1}   61.38{col 50}{space 3}0.000{col 58}{space 4} 1.400542{col 71}{space 3} 1.492941
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     7,044
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2363556{col 30}{space 2} .0391735{col 41}{space 1}    6.03{col 50}{space 3}0.000{col 58}{space 4} .1595769{col 71}{space 3} .3131343
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0188981{col 30}{space 2} .0070877{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0050064{col 71}{space 3} .0327898
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0924504{col 30}{space 2} .1088669{col 41}{space 1}   -0.85{col 50}{space 3}0.396{col 58}{space 4}-.3058256{col 71}{space 3} .1209248
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007114{col 30}{space 2} .0016918{col 41}{space 1}    0.42{col 50}{space 3}0.674{col 58}{space 4}-.0026044{col 71}{space 3} .0040271
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0832876{col 30}{space 2} .0647227{col 41}{space 1}    1.29{col 50}{space 3}0.198{col 58}{space 4}-.0435664{col 71}{space 3} .2101417
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .373014{col 30}{space 2} .0472393{col 41}{space 1}    7.90{col 50}{space 3}0.000{col 58}{space 4} .2804266{col 71}{space 3} .4656013
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2034294{col 30}{space 2}  .088709{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0295629{col 71}{space 3} .3772958
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1610679{col 30}{space 2} .0862589{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0079963{col 71}{space 3} .3301322
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2050398{col 30}{space 2} .0982125{col 41}{space 1}    2.09{col 50}{space 3}0.037{col 58}{space 4} .0125469{col 71}{space 3} .3975328
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2669979{col 30}{space 2} .0845669{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .1012498{col 71}{space 3} .4327461
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1781013{col 30}{space 2} .0752883{col 41}{space 1}   -2.37{col 50}{space 3}0.018{col 58}{space 4}-.3256637{col 71}{space 3}-.0305389
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1834013{col 30}{space 2} .0560747{col 41}{space 1}   -3.27{col 50}{space 3}0.001{col 58}{space 4}-.2933057{col 71}{space 3} -.073497
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0013945{col 30}{space 2} .0018506{col 41}{space 1}   -0.75{col 50}{space 3}0.451{col 58}{space 4}-.0050215{col 71}{space 3} .0022326
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0975972{col 30}{space 2}  .252959{col 41}{space 1}    0.39{col 50}{space 3}0.700{col 58}{space 4}-.3981932{col 71}{space 3} .5933876
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .110065{col 30}{space 2} .1114206{col 41}{space 1}    0.99{col 50}{space 3}0.323{col 58}{space 4}-.1083154{col 71}{space 3} .3284454
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5206236{col 30}{space 2} .1079862{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .3089746{col 71}{space 3} .7322727
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5654602{col 30}{space 2} .1172987{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .3355589{col 71}{space 3} .7953615
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2464165{col 30}{space 2} .1064624{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4}  .037754{col 71}{space 3} .4550789
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .6301199{col 30}{space 2} .0927856{col 41}{space 1}    6.79{col 50}{space 3}0.000{col 58}{space 4} .4482635{col 71}{space 3} .8119763
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3340946{col 30}{space 2} .0450822{col 41}{space 1}   -7.41{col 50}{space 3}0.000{col 58}{space 4}-.4224541{col 71}{space 3}-.2457352
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0171976{col 30}{space 2} .0397492{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0607094{col 71}{space 3} .0951047
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-37166.801}  
Iteration 1:{space 3}log pseudolikelihood = {res:  -37166.8}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    18,429
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   5739.38
{txt}Log pseudolikelihood = {res}  -37166.8{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,218} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0040202{col 30}{space 2} .0032208{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0022925{col 71}{space 3} .0103329
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0032098{col 30}{space 2}  .001026{col 41}{space 1}   -3.13{col 50}{space 3}0.002{col 58}{space 4}-.0052208{col 71}{space 3}-.0011988
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0152607{col 30}{space 2} .0109482{col 41}{space 1}    1.39{col 50}{space 3}0.163{col 58}{space 4}-.0061974{col 71}{space 3} .0367188
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002811{col 30}{space 2} .0002061{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4}-.0001228{col 71}{space 3} .0006849
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0641264{col 30}{space 2} .0076977{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .0490392{col 71}{space 3} .0792136
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .066017{col 30}{space 2} .0066164{col 41}{space 1}    9.98{col 50}{space 3}0.000{col 58}{space 4}  .053049{col 71}{space 3} .0789849
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0110239{col 30}{space 2}  .008208{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.0050635{col 71}{space 3} .0271113
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0524615{col 30}{space 2} .0092238{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .0343831{col 71}{space 3} .0705398
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0247407{col 30}{space 2} .0094982{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0061245{col 71}{space 3} .0433569
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0405172{col 30}{space 2} .0091598{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .0225642{col 71}{space 3} .0584701
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0671301{col 30}{space 2}  .008597{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4} .0502802{col 71}{space 3} .0839799
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0302462{col 30}{space 2} .0121069{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.0539752{col 71}{space 3}-.0065171
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0064732{col 30}{space 2} .0042426{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4}-.0147886{col 71}{space 3} .0018421
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0548563{col 30}{space 2} .0131857{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0290129{col 71}{space 3} .0806997
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} -.014726{col 30}{space 2} .0112566{col 41}{space 1}   -1.31{col 50}{space 3}0.191{col 58}{space 4}-.0367886{col 71}{space 3} .0073366
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1795534{col 30}{space 2} .0139241{col 41}{space 1}   12.90{col 50}{space 3}0.000{col 58}{space 4} .1522627{col 71}{space 3} .2068442
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1972422{col 30}{space 2} .0124909{col 41}{space 1}   15.79{col 50}{space 3}0.000{col 58}{space 4} .1727604{col 71}{space 3}  .221724
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0628733{col 30}{space 2} .0120391{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4} .0392771{col 71}{space 3} .0864696
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0224992{col 30}{space 2} .0112613{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0004274{col 71}{space 3}  .044571
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0302164{col 30}{space 2} .0040135{col 41}{space 1}   -7.53{col 50}{space 3}0.000{col 58}{space 4}-.0380827{col 71}{space 3}-.0223501
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0400561{col 30}{space 2} .0067683{col 41}{space 1}   -5.92{col 50}{space 3}0.000{col 58}{space 4}-.0533217{col 71}{space 3}-.0267905
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.054436{col 30}{space 2} .0068369{col 41}{space 1}   -7.96{col 50}{space 3}0.000{col 58}{space 4} -.067836{col 71}{space 3} -.041036
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0079225{col 30}{space 2}   .00659{col 41}{space 1}   -1.20{col 50}{space 3}0.229{col 58}{space 4}-.0208386{col 71}{space 3} .0049937
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.297242{col 30}{space 2} .0172349{col 41}{space 1}   75.27{col 50}{space 3}0.000{col 58}{space 4} 1.263462{col 71}{space 3} 1.331021
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    18,429
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0210712{col 30}{space 2} .0168824{col 41}{space 1}    1.25{col 50}{space 3}0.212{col 58}{space 4}-.0120178{col 71}{space 3} .0541602
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0168236{col 30}{space 2} .0053811{col 41}{space 1}   -3.13{col 50}{space 3}0.002{col 58}{space 4}-.0273703{col 71}{space 3}-.0062769
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0799868{col 30}{space 2}  .057391{col 41}{space 1}    1.39{col 50}{space 3}0.163{col 58}{space 4}-.0324976{col 71}{space 3} .1924711
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0014732{col 30}{space 2} .0010802{col 41}{space 1}    1.36{col 50}{space 3}0.173{col 58}{space 4} -.000644{col 71}{space 3} .0035904
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3361093{col 30}{space 2} .0403277{col 41}{space 1}    8.33{col 50}{space 3}0.000{col 58}{space 4} .2570685{col 71}{space 3} .4151502
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3460185{col 30}{space 2} .0347025{col 41}{space 1}    9.97{col 50}{space 3}0.000{col 58}{space 4} .2780029{col 71}{space 3} .4140341
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0577802{col 30}{space 2} .0430196{col 41}{space 1}    1.34{col 50}{space 3}0.179{col 58}{space 4}-.0265367{col 71}{space 3} .1420972
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2749695{col 30}{space 2} .0483194{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .1802653{col 71}{space 3} .3696737
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .129675{col 30}{space 2} .0497883{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0320917{col 71}{space 3} .2272582
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2123651{col 30}{space 2} .0480005{col 41}{space 1}    4.42{col 50}{space 3}0.000{col 58}{space 4} .1182858{col 71}{space 3} .3064444
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3518527{col 30}{space 2} .0450499{col 41}{space 1}    7.81{col 50}{space 3}0.000{col 58}{space 4} .2635565{col 71}{space 3} .4401489
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.158531{col 30}{space 2} .0634543{col 41}{space 1}   -2.50{col 50}{space 3}0.012{col 58}{space 4}-.2828991{col 71}{space 3}-.0341629
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0339285{col 30}{space 2} .0222348{col 41}{space 1}   -1.53{col 50}{space 3}0.127{col 58}{space 4} -.077508{col 71}{space 3} .0096509
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2875217{col 30}{space 2}  .069088{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .1521117{col 71}{space 3} .4229316
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0771842{col 30}{space 2} .0589974{col 41}{space 1}   -1.31{col 50}{space 3}0.191{col 58}{space 4} -.192817{col 71}{space 3} .0384485
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .941104{col 30}{space 2} .0730076{col 41}{space 1}   12.89{col 50}{space 3}0.000{col 58}{space 4} .7980117{col 71}{space 3} 1.084196
{txt}electricity_mean {c |}{col 18}{res}{space 2} 1.033817{col 30}{space 2} .0653698{col 41}{space 1}   15.81{col 50}{space 3}0.000{col 58}{space 4} .9056947{col 71}{space 3}  1.16194
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3295416{col 30}{space 2}   .06309{col 41}{space 1}    5.22{col 50}{space 3}0.000{col 58}{space 4} .2058875{col 71}{space 3} .4531957
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1179264{col 30}{space 2} .0590095{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4}   .00227{col 71}{space 3} .2335828
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1583752{col 30}{space 2} .0210377{col 41}{space 1}   -7.53{col 50}{space 3}0.000{col 58}{space 4}-.1996084{col 71}{space 3} -.117142
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.2099485{col 30}{space 2} .0354286{col 41}{space 1}   -5.93{col 50}{space 3}0.000{col 58}{space 4}-.2793873{col 71}{space 3}-.1405097
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.2853185{col 30}{space 2} .0357514{col 41}{space 1}   -7.98{col 50}{space 3}0.000{col 58}{space 4}-.3553899{col 71}{space 3}-.2152471
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0415245{col 30}{space 2} .0345306{col 41}{space 1}   -1.20{col 50}{space 3}0.229{col 58}{space 4}-.1092033{col 71}{space 3} .0261543
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-34315.379}  
Iteration 1:{space 3}log pseudolikelihood = {res:-34315.373}  
Iteration 2:{space 3}log pseudolikelihood = {res:-34315.373}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    17,046
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   7545.21
{txt}Log pseudolikelihood = {res}-34315.373{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:8,817} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0008853{col 30}{space 2} .0035034{col 41}{space 1}    0.25{col 50}{space 3}0.801{col 58}{space 4}-.0059812{col 71}{space 3} .0077518
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0038558{col 30}{space 2} .0017795{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.0073435{col 71}{space 3}-.0003681
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0241054{col 30}{space 2} .0169906{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4}-.0574064{col 71}{space 3} .0091955
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003333{col 30}{space 2} .0002797{col 41}{space 1}   -1.19{col 50}{space 3}0.233{col 58}{space 4}-.0008816{col 71}{space 3}  .000215
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0208935{col 30}{space 2} .0085139{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0042066{col 71}{space 3} .0375805
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .1222409{col 30}{space 2} .0110972{col 41}{space 1}   11.02{col 50}{space 3}0.000{col 58}{space 4} .1004908{col 71}{space 3}  .143991
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0147837{col 30}{space 2} .0141864{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0130212{col 71}{space 3} .0425885
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1125022{col 30}{space 2} .0122128{col 41}{space 1}    9.21{col 50}{space 3}0.000{col 58}{space 4} .0885654{col 71}{space 3} .1364389
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0191441{col 30}{space 2} .0124968{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0053492{col 71}{space 3} .0436374
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0518432{col 30}{space 2} .0086816{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .0348276{col 71}{space 3} .0688588
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .075296{col 30}{space 2}  .009294{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .0570801{col 71}{space 3} .0935119
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0181976{col 30}{space 2} .0081712{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}-.0342128{col 71}{space 3}-.0021823
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0029343{col 30}{space 2} .0023048{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4}-.0074515{col 71}{space 3}  .001583
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0316672{col 30}{space 2} .0105489{col 41}{space 1}   -3.00{col 50}{space 3}0.003{col 58}{space 4}-.0523426{col 71}{space 3}-.0109918
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0964279{col 30}{space 2}  .018094{col 41}{space 1}    5.33{col 50}{space 3}0.000{col 58}{space 4} .0609643{col 71}{space 3} .1318915
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1996701{col 30}{space 2} .0176513{col 41}{space 1}   11.31{col 50}{space 3}0.000{col 58}{space 4} .1650741{col 71}{space 3} .2342661
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1248578{col 30}{space 2} .0154235{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .0946284{col 71}{space 3} .1550872
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .043608{col 30}{space 2} .0124428{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .0192207{col 71}{space 3} .0679954
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1069644{col 30}{space 2} .0126981{col 41}{space 1}    8.42{col 50}{space 3}0.000{col 58}{space 4} .0820766{col 71}{space 3} .1318522
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} -.065717{col 30}{space 2} .0041925{col 41}{space 1}  -15.68{col 50}{space 3}0.000{col 58}{space 4}-.0739341{col 71}{space 3}-.0574999
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0129235{col 30}{space 2} .0077579{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0022818{col 71}{space 3} .0281287
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0115191{col 30}{space 2} .0065364{col 41}{space 1}   -1.76{col 50}{space 3}0.078{col 58}{space 4}-.0243301{col 71}{space 3}  .001292
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0270187{col 30}{space 2} .0075186{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.0417548{col 71}{space 3}-.0122826
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.218535{col 30}{space 2} .0214096{col 41}{space 1}   56.92{col 50}{space 3}0.000{col 58}{space 4} 1.176572{col 71}{space 3} 1.260497
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    17,046
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0040896{col 30}{space 2} .0161836{col 41}{space 1}    0.25{col 50}{space 3}0.800{col 58}{space 4}-.0276296{col 71}{space 3} .0358089
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0178121{col 30}{space 2} .0082231{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4} -.033929{col 71}{space 3}-.0016952
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1113565{col 30}{space 2} .0784861{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4}-.2651865{col 71}{space 3} .0424735
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0015397{col 30}{space 2} .0012919{col 41}{space 1}   -1.19{col 50}{space 3}0.233{col 58}{space 4}-.0040718{col 71}{space 3} .0009924
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0965188{col 30}{space 2} .0393312{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4}  .019431{col 71}{space 3} .1736066
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .564699{col 30}{space 2} .0511976{col 41}{space 1}   11.03{col 50}{space 3}0.000{col 58}{space 4} .4643536{col 71}{space 3} .6650445
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .068294{col 30}{space 2} .0655346{col 41}{space 1}    1.04{col 50}{space 3}0.297{col 58}{space 4}-.0601514{col 71}{space 3} .1967395
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .5197105{col 30}{space 2} .0563856{col 41}{space 1}    9.22{col 50}{space 3}0.000{col 58}{space 4} .4091967{col 71}{space 3} .6302242
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0884374{col 30}{space 2} .0577297{col 41}{space 1}    1.53{col 50}{space 3}0.126{col 58}{space 4}-.0247108{col 71}{space 3} .2015855
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2394929{col 30}{space 2} .0401236{col 41}{space 1}    5.97{col 50}{space 3}0.000{col 58}{space 4} .1608521{col 71}{space 3} .3181336
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3478345{col 30}{space 2} .0429364{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .2636808{col 71}{space 3} .4319882
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0840648{col 30}{space 2} .0377511{col 41}{space 1}   -2.23{col 50}{space 3}0.026{col 58}{space 4}-.1580556{col 71}{space 3}-.0100739
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.013555{col 30}{space 2} .0106442{col 41}{space 1}   -1.27{col 50}{space 3}0.203{col 58}{space 4}-.0344173{col 71}{space 3} .0073073
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.1462885{col 30}{space 2} .0487431{col 41}{space 1}   -3.00{col 50}{space 3}0.003{col 58}{space 4}-.2418233{col 71}{space 3}-.0507538
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .4454543{col 30}{space 2} .0835861{col 41}{space 1}    5.33{col 50}{space 3}0.000{col 58}{space 4} .2816286{col 71}{space 3} .6092801
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .9223878{col 30}{space 2} .0814309{col 41}{space 1}   11.33{col 50}{space 3}0.000{col 58}{space 4} .7627862{col 71}{space 3} 1.081989
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .576788{col 30}{space 2} .0711776{col 41}{space 1}    8.10{col 50}{space 3}0.000{col 58}{space 4} .4372824{col 71}{space 3} .7162936
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2014499{col 30}{space 2} .0574534{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} .0888432{col 71}{space 3} .3140565
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4941283{col 30}{space 2} .0586244{col 41}{space 1}    8.43{col 50}{space 3}0.000{col 58}{space 4} .3792266{col 71}{space 3}   .60903
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.3035836{col 30}{space 2} .0192955{col 41}{space 1}  -15.73{col 50}{space 3}0.000{col 58}{space 4} -.341402{col 71}{space 3}-.2657652
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0597007{col 30}{space 2} .0358443{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0105528{col 71}{space 3} .1299543
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} -.053213{col 30}{space 2} .0302001{col 41}{space 1}   -1.76{col 50}{space 3}0.078{col 58}{space 4}-.1124041{col 71}{space 3} .0059781
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.1248143{col 30}{space 2} .0347948{col 41}{space 1}   -3.59{col 50}{space 3}0.000{col 58}{space 4}-.1930108{col 71}{space 3}-.0566178
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9_purchase  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-40423.347}  
Iteration 1:{space 3}log pseudolikelihood = {res:-40423.335}  
Iteration 2:{space 3}log pseudolikelihood = {res:-40423.335}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    20,293
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   5198.68
{txt}Log pseudolikelihood = {res}-40423.335{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,105} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   hdd9_purchase{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0010507{col 30}{space 2} .0030655{col 41}{space 1}    0.34{col 50}{space 3}0.732{col 58}{space 4}-.0049575{col 71}{space 3} .0070589
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0013434{col 30}{space 2} .0016373{col 41}{space 1}    0.82{col 50}{space 3}0.412{col 58}{space 4}-.0018656{col 71}{space 3} .0045525
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0096115{col 30}{space 2} .0183392{col 41}{space 1}    0.52{col 50}{space 3}0.600{col 58}{space 4}-.0263326{col 71}{space 3} .0455556
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0021655{col 30}{space 2} .0003286{col 41}{space 1}   -6.59{col 50}{space 3}0.000{col 58}{space 4}-.0028095{col 71}{space 3}-.0015215
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0193794{col 30}{space 2} .0099557{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4}-.0001333{col 71}{space 3} .0388921
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0920064{col 30}{space 2} .0106904{col 41}{space 1}    8.61{col 50}{space 3}0.000{col 58}{space 4} .0710535{col 71}{space 3} .1129593
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0530454{col 30}{space 2}  .012509{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .0285282{col 71}{space 3} .0775627
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0835466{col 30}{space 2} .0110108{col 41}{space 1}    7.59{col 50}{space 3}0.000{col 58}{space 4} .0619658{col 71}{space 3} .1051273
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1066204{col 30}{space 2} .0094249{col 41}{space 1}   11.31{col 50}{space 3}0.000{col 58}{space 4}  .088148{col 71}{space 3} .1250928
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .050033{col 30}{space 2} .0078766{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4} .0345951{col 71}{space 3} .0654709
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0729348{col 30}{space 2} .0086271{col 41}{space 1}    8.45{col 50}{space 3}0.000{col 58}{space 4} .0560259{col 71}{space 3} .0898437
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0168254{col 30}{space 2} .0082518{col 41}{space 1}   -2.04{col 50}{space 3}0.041{col 58}{space 4}-.0329985{col 71}{space 3}-.0006522
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0002442{col 30}{space 2} .0007174{col 41}{space 1}   -0.34{col 50}{space 3}0.734{col 58}{space 4}-.0016502{col 71}{space 3} .0011618
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0619425{col 30}{space 2} .0104673{col 41}{space 1}   -5.92{col 50}{space 3}0.000{col 58}{space 4}-.0824581{col 71}{space 3}-.0414269
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0263511{col 30}{space 2} .0204069{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.0136457{col 71}{space 3} .0663479
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1352754{col 30}{space 2} .0197859{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .0964957{col 71}{space 3} .1740551
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0733469{col 30}{space 2}  .017387{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4}  .039269{col 71}{space 3} .1074248
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1096578{col 30}{space 2} .0155836{col 41}{space 1}    7.04{col 50}{space 3}0.000{col 58}{space 4} .0791146{col 71}{space 3}  .140201
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1894961{col 30}{space 2}  .015345{col 41}{space 1}   12.35{col 50}{space 3}0.000{col 58}{space 4} .1594204{col 71}{space 3} .2195717
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0597589{col 30}{space 2} .0043329{col 41}{space 1}  -13.79{col 50}{space 3}0.000{col 58}{space 4}-.0682512{col 71}{space 3}-.0512666
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0480537{col 30}{space 2} .0098818{col 41}{space 1}   -4.86{col 50}{space 3}0.000{col 58}{space 4}-.0674217{col 71}{space 3}-.0286857
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0462461{col 30}{space 2} .0095874{col 41}{space 1}   -4.82{col 50}{space 3}0.000{col 58}{space 4} -.065037{col 71}{space 3}-.0274552
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0486675{col 30}{space 2} .0087236{col 41}{space 1}    5.58{col 50}{space 3}0.000{col 58}{space 4} .0315696{col 71}{space 3} .0657655
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0043538{col 30}{space 2} .0088779{col 41}{space 1}    0.49{col 50}{space 3}0.624{col 58}{space 4}-.0130466{col 71}{space 3} .0217543
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0417335{col 30}{space 2} .0083038{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .0254583{col 71}{space 3} .0580087
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.164022{col 30}{space 2} .0258649{col 41}{space 1}   45.00{col 50}{space 3}0.000{col 58}{space 4} 1.113328{col 71}{space 3} 1.214716
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    20,293
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0041871{col 30}{space 2}  .012216{col 41}{space 1}    0.34{col 50}{space 3}0.732{col 58}{space 4}-.0197558{col 71}{space 3} .0281301
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0053536{col 30}{space 2} .0065244{col 41}{space 1}    0.82{col 50}{space 3}0.412{col 58}{space 4} -.007434{col 71}{space 3} .0181411
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0383016{col 30}{space 2}  .073079{col 41}{space 1}    0.52{col 50}{space 3}0.600{col 58}{space 4}-.1049305{col 71}{space 3} .1815337
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0086294{col 30}{space 2} .0013073{col 41}{space 1}   -6.60{col 50}{space 3}0.000{col 58}{space 4}-.0111916{col 71}{space 3}-.0060671
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0772263{col 30}{space 2} .0396727{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4}-.0005308{col 71}{space 3} .1549834
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3666429{col 30}{space 2} .0426142{col 41}{space 1}    8.60{col 50}{space 3}0.000{col 58}{space 4} .2831207{col 71}{space 3} .4501652
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2113845{col 30}{space 2} .0498508{col 41}{space 1}    4.24{col 50}{space 3}0.000{col 58}{space 4} .1136788{col 71}{space 3} .3090902
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .3329306{col 30}{space 2} .0438522{col 41}{space 1}    7.59{col 50}{space 3}0.000{col 58}{space 4} .2469818{col 71}{space 3} .4188793
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .4248791{col 30}{space 2} .0374741{col 41}{space 1}   11.34{col 50}{space 3}0.000{col 58}{space 4} .3514312{col 71}{space 3}  .498327
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1993801{col 30}{space 2} .0314001{col 41}{space 1}    6.35{col 50}{space 3}0.000{col 58}{space 4}  .137837{col 71}{space 3} .2609232
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .290643{col 30}{space 2} .0343835{col 41}{space 1}    8.45{col 50}{space 3}0.000{col 58}{space 4} .2232525{col 71}{space 3} .3580335
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0670486{col 30}{space 2} .0329038{col 41}{space 1}   -2.04{col 50}{space 3}0.042{col 58}{space 4}-.1315389{col 71}{space 3}-.0025583
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0009731{col 30}{space 2} .0028585{col 41}{space 1}   -0.34{col 50}{space 3}0.734{col 58}{space 4}-.0065756{col 71}{space 3} .0046294
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.2468391{col 30}{space 2} .0416783{col 41}{space 1}   -5.92{col 50}{space 3}0.000{col 58}{space 4}-.3285269{col 71}{space 3}-.1651512
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1050085{col 30}{space 2} .0813277{col 41}{space 1}    1.29{col 50}{space 3}0.197{col 58}{space 4}-.0543908{col 71}{space 3} .2644078
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5390684{col 30}{space 2} .0787712{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .3846796{col 71}{space 3} .6934572
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2922853{col 30}{space 2} .0692706{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1565174{col 71}{space 3} .4280533
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4369832{col 30}{space 2} .0621563{col 41}{space 1}    7.03{col 50}{space 3}0.000{col 58}{space 4} .3151591{col 71}{space 3} .5588073
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .7551363{col 30}{space 2}    .0611{col 41}{space 1}   12.36{col 50}{space 3}0.000{col 58}{space 4} .6353826{col 71}{space 3}   .87489
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2381375{col 30}{space 2} .0172355{col 41}{space 1}  -13.82{col 50}{space 3}0.000{col 58}{space 4}-.2719186{col 71}{space 3}-.2043565
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1914925{col 30}{space 2} .0393331{col 41}{space 1}   -4.87{col 50}{space 3}0.000{col 58}{space 4}-.2685838{col 71}{space 3}-.1144011
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1842893{col 30}{space 2} .0382004{col 41}{space 1}   -4.82{col 50}{space 3}0.000{col 58}{space 4}-.2591608{col 71}{space 3}-.1094178
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1939387{col 30}{space 2} .0347387{col 41}{space 1}    5.58{col 50}{space 3}0.000{col 58}{space 4} .1258522{col 71}{space 3} .2620252
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}   .01735{col 30}{space 2} .0353757{col 41}{space 1}    0.49{col 50}{space 3}0.624{col 58}{space 4}-.0519852{col 71}{space 3} .0866851
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .1663067{col 30}{space 2} .0330837{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .1014638{col 71}{space 3} .2311497
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. 
. esttab using  S23_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean  )
{res}{txt}(note: file S23_poisson.rtf not found)
(output written to {browse  `"S23_poisson.rtf"'})

{com}. restore
{txt}
{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S24                                        *
. ********************************************************************************
. preserve
{txt}
{com}. drop if sum_vill<=1|sum_vill==.
{txt}(24,163 observations deleted)

{com}. 
. drop pdd9_mean no_species_mean hhsize_mean dependent_share_mean head_age_mean female_head_mean head_read_mean motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean weather_shock_mean plot_area_mean other_crop_mean
{txt}
{com}. egen pdd9_mean=mean(pdd9), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_vill=mean(pdd9_vill), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_town=mean(pdd9_town), by(HHID_panel)
{txt}
{com}. egen pdd9_mean_dist=mean(pdd9_dist), by(HHID_panel)
{txt}
{com}. 
. foreach x of varlist hhsize dependent_share head_age female_head head_read  motobike phone  electricity wagejob enterprise weather_shock  plot_area other_crop{c -(}
{txt}  2{com}. egen `x'_mean=mean(`x'), by(HHID_panel)
{txt}  3{com}. {c )-}
{txt}
{com}. 
. 
. *                                  hh_level                                    *
. eststo clear
{txt}
{com}. poisson hdd9  pdd9   $xlist  pdd9_mean i.country i.year  , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-128780.28}  
Iteration 1:{space 3}log pseudolikelihood = {res:-128780.28}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 49}Wald chi2({res}35{txt}){col 67}= {res}  18432.39
{txt}Log pseudolikelihood = {res}-128780.28{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0195902{col 30}{space 2} .0011178{col 41}{space 1}   17.53{col 50}{space 3}0.000{col 58}{space 4} .0173993{col 71}{space 3} .0217811
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0020538{col 30}{space 2} .0004629{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4}-.0029611{col 71}{space 3}-.0011466
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0046565{col 30}{space 2} .0054045{col 41}{space 1}    0.86{col 50}{space 3}0.389{col 58}{space 4}-.0059361{col 71}{space 3} .0152491
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000231{col 30}{space 2}  .000089{col 41}{space 1}    0.26{col 50}{space 3}0.796{col 58}{space 4}-.0001514{col 71}{space 3} .0001975
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0159431{col 30}{space 2} .0032501{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4}  .009573{col 71}{space 3} .0223131
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0659859{col 30}{space 2} .0029174{col 41}{space 1}   22.62{col 50}{space 3}0.000{col 58}{space 4}  .060268{col 71}{space 3} .0717039
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0193754{col 30}{space 2} .0049574{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0096591{col 71}{space 3} .0290917
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .033834{col 30}{space 2}  .003689{col 41}{space 1}    9.17{col 50}{space 3}0.000{col 58}{space 4} .0266038{col 71}{space 3} .0410643
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0274337{col 30}{space 2} .0040334{col 41}{space 1}    6.80{col 50}{space 3}0.000{col 58}{space 4} .0195284{col 71}{space 3}  .035339
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0230485{col 30}{space 2} .0035119{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .0161654{col 71}{space 3} .0299316
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0377541{col 30}{space 2} .0032992{col 41}{space 1}   11.44{col 50}{space 3}0.000{col 58}{space 4} .0312878{col 71}{space 3} .0442204
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0260639{col 30}{space 2} .0028535{col 41}{space 1}   -9.13{col 50}{space 3}0.000{col 58}{space 4}-.0316566{col 71}{space 3}-.0204712
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0003947{col 30}{space 2} .0002258{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.0008372{col 71}{space 3} .0000478
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0275153{col 30}{space 2} .0031979{col 41}{space 1}    8.60{col 50}{space 3}0.000{col 58}{space 4} .0212476{col 71}{space 3}  .033783
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0013295{col 30}{space 2} .0066647{col 41}{space 1}    0.20{col 50}{space 3}0.842{col 58}{space 4}-.0117332{col 71}{space 3} .0143921
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .112005{col 30}{space 2} .0053884{col 41}{space 1}   20.79{col 50}{space 3}0.000{col 58}{space 4} .1014439{col 71}{space 3} .1225661
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1192292{col 30}{space 2} .0054997{col 41}{space 1}   21.68{col 50}{space 3}0.000{col 58}{space 4} .1084499{col 71}{space 3} .1300084
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0300702{col 30}{space 2} .0051802{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .0199172{col 71}{space 3} .0402232
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0330529{col 30}{space 2} .0046689{col 41}{space 1}    7.08{col 50}{space 3}0.000{col 58}{space 4} .0239021{col 71}{space 3} .0422037
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0022997{col 30}{space 2} .0014768{col 41}{space 1}   -1.56{col 50}{space 3}0.119{col 58}{space 4}-.0051942{col 71}{space 3} .0005949
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.0897718{col 30}{space 2}  .005884{col 41}{space 1}  -15.26{col 50}{space 3}0.000{col 58}{space 4}-.1013041{col 71}{space 3}-.0782394
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.3202018{col 30}{space 2} .0062633{col 41}{space 1}  -51.12{col 50}{space 3}0.000{col 58}{space 4}-.3324777{col 71}{space 3}-.3079259
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.1018468{col 30}{space 2} .0058127{col 41}{space 1}  -17.52{col 50}{space 3}0.000{col 58}{space 4}-.1132395{col 71}{space 3} -.090454
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.0652991{col 30}{space 2} .0056991{col 41}{space 1}  -11.46{col 50}{space 3}0.000{col 58}{space 4}-.0764691{col 71}{space 3} -.054129
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .0567026{col 30}{space 2} .0071416{col 41}{space 1}    7.94{col 50}{space 3}0.000{col 58}{space 4} .0427052{col 71}{space 3} .0706999
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0483906{col 30}{space 2} .0089101{col 41}{space 1}   -5.43{col 50}{space 3}0.000{col 58}{space 4} -.065854{col 71}{space 3}-.0309271
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0000511{col 30}{space 2} .0065248{col 41}{space 1}   -0.01{col 50}{space 3}0.994{col 58}{space 4}-.0128396{col 71}{space 3} .0127373
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0047421{col 30}{space 2} .0073678{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.0191826{col 71}{space 3} .0096985
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0024116{col 30}{space 2} .0065894{col 41}{space 1}    0.37{col 50}{space 3}0.714{col 58}{space 4}-.0105034{col 71}{space 3} .0153265
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0134727{col 30}{space 2} .0073417{col 41}{space 1}    1.84{col 50}{space 3}0.066{col 58}{space 4}-.0009167{col 71}{space 3} .0278622
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0297918{col 30}{space 2} .0073456{col 41}{space 1}   -4.06{col 50}{space 3}0.000{col 58}{space 4}-.0441889{col 71}{space 3}-.0153947
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0254743{col 30}{space 2} .0070795{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0115986{col 71}{space 3} .0393499
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0391538{col 30}{space 2} .0105012{col 41}{space 1}   -3.73{col 50}{space 3}0.000{col 58}{space 4}-.0597358{col 71}{space 3}-.0185717
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0725642{col 30}{space 2} .0073126{col 41}{space 1}    9.92{col 50}{space 3}0.000{col 58}{space 4} .0582317{col 71}{space 3} .0868967
{txt}{space 11}2019  {c |}{col 18}{res}{space 2} -.018821{col 30}{space 2} .0072115{col 41}{space 1}   -2.61{col 50}{space 3}0.009{col 58}{space 4}-.0329553{col 71}{space 3}-.0046868
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.523935{col 30}{space 2} .0101516{col 41}{space 1}  150.12{col 50}{space 3}0.000{col 58}{space 4} 1.504039{col 71}{space 3} 1.543832
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1069624{col 30}{space 2} .0060982{col 41}{space 1}   17.54{col 50}{space 3}0.000{col 58}{space 4}   .09501{col 71}{space 3} .1189147
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.011214{col 30}{space 2} .0025276{col 41}{space 1}   -4.44{col 50}{space 3}0.000{col 58}{space 4} -.016168{col 71}{space 3}-.0062599
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0254245{col 30}{space 2} .0295079{col 41}{space 1}    0.86{col 50}{space 3}0.389{col 58}{space 4}  -.03241{col 71}{space 3}  .083259
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0001259{col 30}{space 2}  .000486{col 41}{space 1}    0.26{col 50}{space 3}0.796{col 58}{space 4}-.0008266{col 71}{space 3} .0010783
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .087049{col 30}{space 2} .0177462{col 41}{space 1}    4.91{col 50}{space 3}0.000{col 58}{space 4}  .052267{col 71}{space 3} .1218311
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3602829{col 30}{space 2} .0159275{col 41}{space 1}   22.62{col 50}{space 3}0.000{col 58}{space 4} .3290655{col 71}{space 3} .3915003
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1057896{col 30}{space 2} .0270668{col 41}{space 1}    3.91{col 50}{space 3}0.000{col 58}{space 4} .0527396{col 71}{space 3} .1588395
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1847337{col 30}{space 2} .0201396{col 41}{space 1}    9.17{col 50}{space 3}0.000{col 58}{space 4} .1452607{col 71}{space 3} .2242067
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1497879{col 30}{space 2} .0220209{col 41}{space 1}    6.80{col 50}{space 3}0.000{col 58}{space 4} .1066277{col 71}{space 3} .1929482
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1258449{col 30}{space 2} .0191749{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .0882628{col 71}{space 3}  .163427
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .206137{col 30}{space 2} .0180146{col 41}{space 1}   11.44{col 50}{space 3}0.000{col 58}{space 4} .1708291{col 71}{space 3}  .241445
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1423087{col 30}{space 2} .0155806{col 41}{space 1}   -9.13{col 50}{space 3}0.000{col 58}{space 4}-.1728462{col 71}{space 3}-.1117713
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0021551{col 30}{space 2} .0012328{col 41}{space 1}   -1.75{col 50}{space 3}0.080{col 58}{space 4}-.0045713{col 71}{space 3} .0002612
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1502334{col 30}{space 2} .0174622{col 41}{space 1}    8.60{col 50}{space 3}0.000{col 58}{space 4} .1160081{col 71}{space 3} .1844587
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0072588{col 30}{space 2} .0363894{col 41}{space 1}    0.20{col 50}{space 3}0.842{col 58}{space 4}-.0640632{col 71}{space 3} .0785808
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .6115466{col 30}{space 2} .0294021{col 41}{space 1}   20.80{col 50}{space 3}0.000{col 58}{space 4} .5539196{col 71}{space 3} .6691737
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6509906{col 30}{space 2} .0300031{col 41}{space 1}   21.70{col 50}{space 3}0.000{col 58}{space 4} .5921857{col 71}{space 3} .7097955
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1641831{col 30}{space 2} .0282851{col 41}{space 1}    5.80{col 50}{space 3}0.000{col 58}{space 4} .1087454{col 71}{space 3} .2196208
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1804686{col 30}{space 2} .0254894{col 41}{space 1}    7.08{col 50}{space 3}0.000{col 58}{space 4} .1305104{col 71}{space 3} .2304269
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0125561{col 30}{space 2} .0080635{col 41}{space 1}   -1.56{col 50}{space 3}0.119{col 58}{space 4}-.0283604{col 71}{space 3} .0032481
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.5200608{col 30}{space 2} .0345953{col 41}{space 1}  -15.03{col 50}{space 3}0.000{col 58}{space 4}-.5878662{col 71}{space 3}-.4522553
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2} -1.65962{col 30}{space 2} .0336678{col 41}{space 1}  -49.29{col 50}{space 3}0.000{col 58}{space 4}-1.725608{col 71}{space 3}-1.593633
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} -.586518{col 30}{space 2} .0341271{col 41}{space 1}  -17.19{col 50}{space 3}0.000{col 58}{space 4}-.6534059{col 71}{space 3}-.5196301
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.3828836{col 30}{space 2} .0337908{col 41}{space 1}  -11.33{col 50}{space 3}0.000{col 58}{space 4}-.4491122{col 71}{space 3}-.3166549
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2}  .353375{col 30}{space 2} .0446364{col 41}{space 1}    7.92{col 50}{space 3}0.000{col 58}{space 4} .2658892{col 71}{space 3} .4408608
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2564313{col 30}{space 2} .0472935{col 41}{space 1}   -5.42{col 50}{space 3}0.000{col 58}{space 4}-.3491249{col 71}{space 3}-.1637376
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0002776{col 30}{space 2} .0354195{col 41}{space 1}   -0.01{col 50}{space 3}0.994{col 58}{space 4}-.0696985{col 71}{space 3} .0691433
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0256812{col 30}{space 2} .0399533{col 41}{space 1}   -0.64{col 50}{space 3}0.520{col 58}{space 4}-.1039882{col 71}{space 3} .0526259
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0131068{col 30}{space 2} .0357843{col 41}{space 1}    0.37{col 50}{space 3}0.714{col 58}{space 4}-.0570291{col 71}{space 3} .0832427
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0736308{col 30}{space 2} .0399743{col 41}{space 1}    1.84{col 50}{space 3}0.065{col 58}{space 4}-.0047174{col 71}{space 3} .1519791
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.1593381{col 30}{space 2} .0395544{col 41}{space 1}   -4.03{col 50}{space 3}0.000{col 58}{space 4}-.2368633{col 71}{space 3}-.0818129
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1400623{col 30}{space 2} .0386005{col 41}{space 1}    3.63{col 50}{space 3}0.000{col 58}{space 4} .0644068{col 71}{space 3} .2157178
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2084371{col 30}{space 2} .0556451{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.3174995{col 71}{space 3}-.0993747
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4085554{col 30}{space 2} .0403849{col 41}{space 1}   10.12{col 50}{space 3}0.000{col 58}{space 4} .3294024{col 71}{space 3} .4877084
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1012136{col 30}{space 2}  .038977{col 41}{space 1}   -2.60{col 50}{space 3}0.009{col 58}{space 4}-.1776071{col 71}{space 3}-.0248202
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-20906.802}  
Iteration 1:{space 3}log pseudolikelihood = {res:-20906.802}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   2480.01
{txt}Log pseudolikelihood = {res}-20906.802{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0120102{col 30}{space 2} .0026663{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0067843{col 71}{space 3} .0172361
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0066337{col 30}{space 2} .0017672{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0031701{col 71}{space 3} .0100974
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0101986{col 30}{space 2} .0148289{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.0392627{col 71}{space 3} .0188656
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0012443{col 30}{space 2} .0002492{col 41}{space 1}   -4.99{col 50}{space 3}0.000{col 58}{space 4}-.0017327{col 71}{space 3}-.0007559
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0040221{col 30}{space 2} .0089773{col 41}{space 1}    0.45{col 50}{space 3}0.654{col 58}{space 4}-.0135732{col 71}{space 3} .0216173
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0953698{col 30}{space 2} .0075976{col 41}{space 1}   12.55{col 50}{space 3}0.000{col 58}{space 4} .0804787{col 71}{space 3} .1102609
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0493695{col 30}{space 2}  .032459{col 41}{space 1}   -1.52{col 50}{space 3}0.128{col 58}{space 4} -.112988{col 71}{space 3} .0142489
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0421361{col 30}{space 2} .0089294{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .0246349{col 71}{space 3} .0596374
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0402433{col 30}{space 2} .0106263{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .0194162{col 71}{space 3} .0610704
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0176954{col 30}{space 2} .0133545{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0084789{col 71}{space 3} .0438698
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .051868{col 30}{space 2} .0114169{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .0294914{col 71}{space 3} .0742446
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0594341{col 30}{space 2} .0079213{col 41}{space 1}   -7.50{col 50}{space 3}0.000{col 58}{space 4}-.0749595{col 71}{space 3}-.0439087
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0017215{col 30}{space 2} .0008781{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} 4.03e-07{col 71}{space 3} .0034425
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0657222{col 30}{space 2} .0077467{col 41}{space 1}    8.48{col 50}{space 3}0.000{col 58}{space 4} .0505389{col 71}{space 3} .0809055
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1925382{col 30}{space 2} .0506998{col 41}{space 1}    3.80{col 50}{space 3}0.000{col 58}{space 4} .0931684{col 71}{space 3} .2919081
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1058791{col 30}{space 2} .0133887{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .0796378{col 71}{space 3} .1321204
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1041887{col 30}{space 2} .0154899{col 41}{space 1}    6.73{col 50}{space 3}0.000{col 58}{space 4}  .073829{col 71}{space 3} .1345484
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .110791{col 30}{space 2} .0203375{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .0709302{col 71}{space 3} .1506517
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .022719{col 30}{space 2} .0144906{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0056821{col 71}{space 3}   .05112
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}  .012718{col 30}{space 2} .0035465{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4}  .005767{col 71}{space 3}  .019669
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0316574{col 30}{space 2} .0053402{col 41}{space 1}   -5.93{col 50}{space 3}0.000{col 58}{space 4} -.042124{col 71}{space 3}-.0211907
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.188818{col 30}{space 2} .0173185{col 41}{space 1}   68.64{col 50}{space 3}0.000{col 58}{space 4} 1.154874{col 71}{space 3} 1.222761
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2}  .050805{col 30}{space 2} .0112791{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0286984{col 71}{space 3} .0729116
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0280617{col 30}{space 2} .0074737{col 41}{space 1}    3.75{col 50}{space 3}0.000{col 58}{space 4} .0134135{col 71}{space 3} .0427098
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0431414{col 30}{space 2} .0627262{col 41}{space 1}   -0.69{col 50}{space 3}0.492{col 58}{space 4}-.1660825{col 71}{space 3} .0797996
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0052636{col 30}{space 2} .0010544{col 41}{space 1}   -4.99{col 50}{space 3}0.000{col 58}{space 4}-.0073302{col 71}{space 3} -.003197
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .017014{col 30}{space 2} .0379758{col 41}{space 1}    0.45{col 50}{space 3}0.654{col 58}{space 4}-.0574172{col 71}{space 3} .0914451
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4034286{col 30}{space 2}  .032186{col 41}{space 1}   12.53{col 50}{space 3}0.000{col 58}{space 4} .3403451{col 71}{space 3}  .466512
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2088405{col 30}{space 2} .1373107{col 41}{space 1}   -1.52{col 50}{space 3}0.128{col 58}{space 4}-.4779646{col 71}{space 3} .0602836
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1782421{col 30}{space 2} .0377802{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .1041943{col 71}{space 3} .2522898
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1702353{col 30}{space 2} .0449411{col 41}{space 1}    3.79{col 50}{space 3}0.000{col 58}{space 4} .0821523{col 71}{space 3} .2583183
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0748543{col 30}{space 2}   .05649{col 41}{space 1}    1.33{col 50}{space 3}0.185{col 58}{space 4}-.0358641{col 71}{space 3} .1855728
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2194094{col 30}{space 2}  .048294{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1247548{col 71}{space 3} .3140639
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2514151{col 30}{space 2} .0335135{col 41}{space 1}   -7.50{col 50}{space 3}0.000{col 58}{space 4}-.3171003{col 71}{space 3}  -.18573
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .007282{col 30}{space 2} .0037142{col 41}{space 1}    1.96{col 50}{space 3}0.050{col 58}{space 4} 2.39e-06{col 71}{space 3} .0145616
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2780146{col 30}{space 2} .0327927{col 41}{space 1}    8.48{col 50}{space 3}0.000{col 58}{space 4} .2137421{col 71}{space 3} .3422871
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .8144655{col 30}{space 2} .2144834{col 41}{space 1}    3.80{col 50}{space 3}0.000{col 58}{space 4} .3940857{col 71}{space 3} 1.234845
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4478844{col 30}{space 2} .0566689{col 41}{space 1}    7.90{col 50}{space 3}0.000{col 58}{space 4} .3368154{col 71}{space 3} .5589534
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4407338{col 30}{space 2} .0655549{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .3122485{col 71}{space 3} .5692191
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4686624{col 30}{space 2} .0859795{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4} .3001457{col 71}{space 3} .6371791
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0961047{col 30}{space 2} .0612902{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0240219{col 71}{space 3} .2162313
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0537991{col 30}{space 2} .0150002{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .0243994{col 71}{space 3} .0831989
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1339154{col 30}{space 2} .0225739{col 41}{space 1}   -5.93{col 50}{space 3}0.000{col 58}{space 4}-.1781593{col 71}{space 3}-.0896714
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_MALAWI if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-9223.7149}  
Iteration 1:{space 3}log pseudolikelihood = {res:-9223.7145}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   1536.46
{txt}Log pseudolikelihood = {res}-9223.7145{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0213484{col 30}{space 2} .0032496{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .0149792{col 71}{space 3} .0277175
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0031275{col 30}{space 2} .0020625{col 41}{space 1}   -1.52{col 50}{space 3}0.129{col 58}{space 4}  -.00717{col 71}{space 3}  .000915
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0456262{col 30}{space 2} .0184853{col 41}{space 1}   -2.47{col 50}{space 3}0.014{col 58}{space 4}-.0818568{col 71}{space 3}-.0093957
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0004251{col 30}{space 2} .0003035{col 41}{space 1}   -1.40{col 50}{space 3}0.161{col 58}{space 4}-.0010199{col 71}{space 3} .0001697
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0176202{col 30}{space 2} .0110037{col 41}{space 1}   -1.60{col 50}{space 3}0.109{col 58}{space 4} -.039187{col 71}{space 3} .0039466
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0603198{col 30}{space 2} .0109525{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .0388533{col 71}{space 3} .0817863
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}  .042255{col 30}{space 2} .0279386{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0125037{col 71}{space 3} .0970138
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0172173{col 30}{space 2} .0119191{col 41}{space 1}    1.44{col 50}{space 3}0.149{col 58}{space 4}-.0061436{col 71}{space 3} .0405782
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0333653{col 30}{space 2} .0202746{col 41}{space 1}    1.65{col 50}{space 3}0.100{col 58}{space 4}-.0063722{col 71}{space 3} .0731027
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0244744{col 30}{space 2} .0131636{col 41}{space 1}    1.86{col 50}{space 3}0.063{col 58}{space 4}-.0013257{col 71}{space 3} .0502745
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0400691{col 30}{space 2} .0092825{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0218757{col 71}{space 3} .0582626
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0361142{col 30}{space 2} .0079944{col 41}{space 1}   -4.52{col 50}{space 3}0.000{col 58}{space 4} -.051783{col 71}{space 3}-.0204453
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0053512{col 30}{space 2} .0050689{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0045837{col 71}{space 3} .0152861
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} -.001078{col 30}{space 2} .0110401{col 41}{space 1}   -0.10{col 50}{space 3}0.922{col 58}{space 4}-.0227162{col 71}{space 3} .0205603
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0013568{col 30}{space 2} .0493335{col 41}{space 1}    0.03{col 50}{space 3}0.978{col 58}{space 4}-.0953351{col 71}{space 3} .0980487
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1279495{col 30}{space 2} .0185021{col 41}{space 1}    6.92{col 50}{space 3}0.000{col 58}{space 4}  .091686{col 71}{space 3} .1642131
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1348991{col 30}{space 2} .0259147{col 41}{space 1}    5.21{col 50}{space 3}0.000{col 58}{space 4} .0841073{col 71}{space 3} .1856909
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0637585{col 30}{space 2} .0184359{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .0276249{col 71}{space 3} .0998921
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0572401{col 30}{space 2} .0163683{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .0251588{col 71}{space 3} .0893213
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0023871{col 30}{space 2} .0048796{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.0119509{col 71}{space 3} .0071767
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0425325{col 30}{space 2} .0091815{col 41}{space 1}    4.63{col 50}{space 3}0.000{col 58}{space 4} .0245371{col 71}{space 3}  .060528
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0158938{col 30}{space 2} .0084698{col 41}{space 1}    1.88{col 50}{space 3}0.061{col 58}{space 4}-.0007067{col 71}{space 3} .0324944
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.594404{col 30}{space 2} .0254993{col 41}{space 1}   62.53{col 50}{space 3}0.000{col 58}{space 4} 1.544426{col 71}{space 3} 1.644382
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1272918{col 30}{space 2} .0193452{col 41}{space 1}    6.58{col 50}{space 3}0.000{col 58}{space 4}  .089376{col 71}{space 3} .1652077
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.018648{col 30}{space 2} .0122908{col 41}{space 1}   -1.52{col 50}{space 3}0.129{col 58}{space 4}-.0427375{col 71}{space 3} .0054414
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2720511{col 30}{space 2} .1103379{col 41}{space 1}   -2.47{col 50}{space 3}0.014{col 58}{space 4}-.4883095{col 71}{space 3}-.0557928
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0025347{col 30}{space 2} .0018088{col 41}{space 1}   -1.40{col 50}{space 3}0.161{col 58}{space 4}-.0060799{col 71}{space 3} .0010105
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.1050622{col 30}{space 2} .0655674{col 41}{space 1}   -1.60{col 50}{space 3}0.109{col 58}{space 4}-.2335719{col 71}{space 3} .0234475
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3596628{col 30}{space 2} .0652746{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4}  .231727{col 71}{space 3} .4875986
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2519501{col 30}{space 2} .1666176{col 41}{space 1}    1.51{col 50}{space 3}0.130{col 58}{space 4}-.0746145{col 71}{space 3} .5785146
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1026599{col 30}{space 2} .0710594{col 41}{space 1}    1.44{col 50}{space 3}0.149{col 58}{space 4}-.0366139{col 71}{space 3} .2419338
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .198944{col 30}{space 2} .1208542{col 41}{space 1}    1.65{col 50}{space 3}0.100{col 58}{space 4} -.037926{col 71}{space 3} .4358139
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1459314{col 30}{space 2} .0785077{col 41}{space 1}    1.86{col 50}{space 3}0.063{col 58}{space 4}-.0079409{col 71}{space 3} .2998037
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2389163{col 30}{space 2} .0552972{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .1305358{col 71}{space 3} .3472968
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2153344{col 30}{space 2} .0476765{col 41}{space 1}   -4.52{col 50}{space 3}0.000{col 58}{space 4}-.3087785{col 71}{space 3}-.1218902
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0319071{col 30}{space 2} .0302288{col 41}{space 1}    1.06{col 50}{space 3}0.291{col 58}{space 4}-.0273402{col 71}{space 3} .0911544
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}-.0064276{col 30}{space 2} .0658279{col 41}{space 1}   -0.10{col 50}{space 3}0.922{col 58}{space 4}-.1354479{col 71}{space 3} .1225927
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0080902{col 30}{space 2} .2941541{col 41}{space 1}    0.03{col 50}{space 3}0.978{col 58}{space 4}-.5684413{col 71}{space 3} .5846217
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7629121{col 30}{space 2} .1104479{col 41}{space 1}    6.91{col 50}{space 3}0.000{col 58}{space 4} .5464383{col 71}{space 3}  .979386
{txt}electricity_mean {c |}{col 18}{res}{space 2} .8043498{col 30}{space 2} .1544177{col 41}{space 1}    5.21{col 50}{space 3}0.000{col 58}{space 4} .5016966{col 71}{space 3} 1.107003
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3801665{col 30}{space 2} .1098264{col 41}{space 1}    3.46{col 50}{space 3}0.001{col 58}{space 4} .1649107{col 71}{space 3} .5954224
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3412998{col 30}{space 2} .0976074{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .1499928{col 71}{space 3} .5326067
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0142333{col 30}{space 2} .0290946{col 41}{space 1}   -0.49{col 50}{space 3}0.625{col 58}{space 4}-.0712577{col 71}{space 3} .0427911
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2536046{col 30}{space 2}   .05462{col 41}{space 1}    4.64{col 50}{space 3}0.000{col 58}{space 4} .1465513{col 71}{space 3} .3606578
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0947685{col 30}{space 2} .0504903{col 41}{space 1}    1.88{col 50}{space 3}0.061{col 58}{space 4}-.0041907{col 71}{space 3} .1937277
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-13051.746}  
Iteration 1:{space 3}log pseudolikelihood = {res:-13051.746}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 49}Wald chi2({res}21{txt}){col 67}= {res}   1382.48
{txt}Log pseudolikelihood = {res}-13051.746{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0434586{col 30}{space 2} .0063652{col 41}{space 1}    6.83{col 50}{space 3}0.000{col 58}{space 4}  .030983{col 71}{space 3} .0559341
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0026208{col 30}{space 2} .0011467{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0003732{col 71}{space 3} .0048684
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0256066{col 30}{space 2} .0179598{col 41}{space 1}   -1.43{col 50}{space 3}0.154{col 58}{space 4}-.0608071{col 71}{space 3} .0095939
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  .000489{col 30}{space 2} .0002623{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4} -.000025{col 71}{space 3} .0010031
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0136133{col 30}{space 2} .0107516{col 41}{space 1}    1.27{col 50}{space 3}0.205{col 58}{space 4}-.0074595{col 71}{space 3} .0346861
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0611766{col 30}{space 2} .0079332{col 41}{space 1}    7.71{col 50}{space 3}0.000{col 58}{space 4} .0456279{col 71}{space 3} .0767253
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0490516{col 30}{space 2} .0182369{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0133079{col 71}{space 3} .0847954
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0157702{col 30}{space 2} .0143759{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0124061{col 71}{space 3} .0439465
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0519729{col 30}{space 2}  .020266{col 41}{space 1}    2.56{col 50}{space 3}0.010{col 58}{space 4} .0122523{col 71}{space 3} .0916935
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0342498{col 30}{space 2} .0154828{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0039042{col 71}{space 3} .0645955
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0310475{col 30}{space 2} .0125528{col 41}{space 1}   -2.47{col 50}{space 3}0.013{col 58}{space 4}-.0556505{col 71}{space 3}-.0064444
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0284519{col 30}{space 2} .0085841{col 41}{space 1}   -3.31{col 50}{space 3}0.001{col 58}{space 4}-.0452765{col 71}{space 3}-.0116273
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0003953{col 30}{space 2} .0003008{col 41}{space 1}   -1.31{col 50}{space 3}0.189{col 58}{space 4}-.0009848{col 71}{space 3} .0001942
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0367234{col 30}{space 2} .0371269{col 41}{space 1}    0.99{col 50}{space 3}0.323{col 58}{space 4} -.036044{col 71}{space 3} .1094909
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0061998{col 30}{space 2} .0219041{col 41}{space 1}    0.28{col 50}{space 3}0.777{col 58}{space 4}-.0367314{col 71}{space 3} .0491309
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .064463{col 30}{space 2} .0175776{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0300115{col 71}{space 3} .0989145
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0609142{col 30}{space 2} .0230707{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4} .0156964{col 71}{space 3}  .106132
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0344824{col 30}{space 2} .0190493{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0028535{col 71}{space 3} .0718182
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0836868{col 30}{space 2} .0153507{col 41}{space 1}    5.45{col 50}{space 3}0.000{col 58}{space 4}    .0536{col 71}{space 3} .1137736
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0454492{col 30}{space 2}  .007281{col 41}{space 1}   -6.24{col 50}{space 3}0.000{col 58}{space 4}-.0597197{col 71}{space 3}-.0311786
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0444166{col 30}{space 2} .0068957{col 41}{space 1}    6.44{col 50}{space 3}0.000{col 58}{space 4} .0309012{col 71}{space 3}  .057932
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  1.53691{col 30}{space 2} .0205229{col 41}{space 1}   74.89{col 50}{space 3}0.000{col 58}{space 4} 1.496686{col 71}{space 3} 1.577135
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .2444944{col 30}{space 2} .0357666{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4}  .174393{col 71}{space 3} .3145957
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0147445{col 30}{space 2} .0064501{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0021026{col 71}{space 3} .0273865
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1440605{col 30}{space 2} .1010539{col 41}{space 1}   -1.43{col 50}{space 3}0.154{col 58}{space 4}-.3421226{col 71}{space 3} .0540016
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0027512{col 30}{space 2} .0014754{col 41}{space 1}    1.86{col 50}{space 3}0.062{col 58}{space 4}-.0001405{col 71}{space 3} .0056429
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0765872{col 30}{space 2} .0604875{col 41}{space 1}    1.27{col 50}{space 3}0.205{col 58}{space 4}-.0419662{col 71}{space 3} .1951406
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3441746{col 30}{space 2} .0445863{col 41}{space 1}    7.72{col 50}{space 3}0.000{col 58}{space 4}  .256787{col 71}{space 3} .4315622
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2759605{col 30}{space 2} .1025692{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0749286{col 71}{space 3} .4769925
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0887218{col 30}{space 2}  .080872{col 41}{space 1}    1.10{col 50}{space 3}0.273{col 58}{space 4}-.0697844{col 71}{space 3}  .247228
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2923951{col 30}{space 2} .1139998{col 41}{space 1}    2.56{col 50}{space 3}0.010{col 58}{space 4} .0689595{col 71}{space 3} .5158307
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1926866{col 30}{space 2} .0871122{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0219499{col 71}{space 3} .3634234
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1746706{col 30}{space 2} .0706008{col 41}{space 1}   -2.47{col 50}{space 3}0.013{col 58}{space 4}-.3130456{col 71}{space 3}-.0362957
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1600681{col 30}{space 2} .0483006{col 41}{space 1}   -3.31{col 50}{space 3}0.001{col 58}{space 4}-.2547356{col 71}{space 3}-.0654006
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.002224{col 30}{space 2} .0016923{col 41}{space 1}   -1.31{col 50}{space 3}0.189{col 58}{space 4}-.0055408{col 71}{space 3} .0010928
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .206603{col 30}{space 2} .2088703{col 41}{space 1}    0.99{col 50}{space 3}0.323{col 58}{space 4}-.2027753{col 71}{space 3} .6159814
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0348793{col 30}{space 2} .1232323{col 41}{space 1}    0.28{col 50}{space 3}0.777{col 58}{space 4}-.2066515{col 71}{space 3} .2764102
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3626635{col 30}{space 2}  .098874{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .1688741{col 71}{space 3}  .556453
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3426981{col 30}{space 2} .1297734{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4}  .088347{col 71}{space 3} .5970493
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1939949{col 30}{space 2} .1071532{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.0160215{col 71}{space 3} .4040113
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4708149{col 30}{space 2} .0862602{col 41}{space 1}    5.46{col 50}{space 3}0.000{col 58}{space 4} .3017481{col 71}{space 3} .6398817
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.2556932{col 30}{space 2} .0409276{col 41}{space 1}   -6.25{col 50}{space 3}0.000{col 58}{space 4}-.3359099{col 71}{space 3}-.1754766
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .249884{col 30}{space 2} .0386776{col 41}{space 1}    6.46{col 50}{space 3}0.000{col 58}{space 4} .1740772{col 71}{space 3} .3256907
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-30016.657}  
Iteration 1:{space 3}log pseudolikelihood = {res:-30016.657}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   3778.70
{txt}Log pseudolikelihood = {res}-30016.657{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0138193{col 30}{space 2} .0026768{col 41}{space 1}    5.16{col 50}{space 3}0.000{col 58}{space 4} .0085729{col 71}{space 3} .0190657
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  -.00569{col 30}{space 2} .0008406{col 41}{space 1}   -6.77{col 50}{space 3}0.000{col 58}{space 4}-.0073376{col 71}{space 3}-.0040424
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0260642{col 30}{space 2} .0095806{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0072866{col 71}{space 3} .0448418
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0009632{col 30}{space 2}  .000174{col 41}{space 1}    5.53{col 50}{space 3}0.000{col 58}{space 4} .0006221{col 71}{space 3} .0013043
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0657025{col 30}{space 2} .0066844{col 41}{space 1}    9.83{col 50}{space 3}0.000{col 58}{space 4} .0526013{col 71}{space 3} .0788038
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0430493{col 30}{space 2} .0053617{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .0325406{col 71}{space 3}  .053558
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0030888{col 30}{space 2} .0072988{col 41}{space 1}    0.42{col 50}{space 3}0.672{col 58}{space 4}-.0112166{col 71}{space 3} .0173941
{txt}{space 11}phone {c |}{col 18}{res}{space 2}   .03234{col 30}{space 2} .0075692{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0175047{col 71}{space 3} .0471753
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0136061{col 30}{space 2} .0084292{col 41}{space 1}    1.61{col 50}{space 3}0.106{col 58}{space 4}-.0029149{col 71}{space 3}  .030127
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0423349{col 30}{space 2} .0093206{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .0240669{col 71}{space 3} .0606029
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0550329{col 30}{space 2} .0076453{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4} .0400485{col 71}{space 3} .0700173
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0012952{col 30}{space 2} .0086951{col 41}{space 1}    0.15{col 50}{space 3}0.882{col 58}{space 4}-.0157469{col 71}{space 3} .0183373
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0027545{col 30}{space 2} .0018106{col 41}{space 1}   -1.52{col 50}{space 3}0.128{col 58}{space 4}-.0063032{col 71}{space 3} .0007942
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0649143{col 30}{space 2} .0099937{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .0453269{col 71}{space 3} .0845016
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .015619{col 30}{space 2} .0097795{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0035485{col 71}{space 3} .0347865
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1488723{col 30}{space 2} .0110811{col 41}{space 1}   13.43{col 50}{space 3}0.000{col 58}{space 4} .1271538{col 71}{space 3} .1705907
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1364292{col 30}{space 2} .0104983{col 41}{space 1}   13.00{col 50}{space 3}0.000{col 58}{space 4} .1158528{col 71}{space 3} .1570056
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0209273{col 30}{space 2} .0120668{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0027233{col 71}{space 3} .0445778
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0135069{col 30}{space 2} .0097118{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.0325417{col 71}{space 3} .0055278
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0048217{col 30}{space 2} .0034268{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4} -.011538{col 71}{space 3} .0018946
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0929138{col 30}{space 2} .0057596{col 41}{space 1}  -16.13{col 50}{space 3}0.000{col 58}{space 4}-.1042025{col 71}{space 3}-.0816251
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0851384{col 30}{space 2} .0058668{col 41}{space 1}  -14.51{col 50}{space 3}0.000{col 58}{space 4}-.0966372{col 71}{space 3}-.0736396
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0608731{col 30}{space 2} .0057381{col 41}{space 1}  -10.61{col 50}{space 3}0.000{col 58}{space 4}-.0721197{col 71}{space 3}-.0496266
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.492519{col 30}{space 2} .0145181{col 41}{space 1}  102.80{col 50}{space 3}0.000{col 58}{space 4} 1.464064{col 71}{space 3} 1.520974
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0804506{col 30}{space 2} .0155822{col 41}{space 1}    5.16{col 50}{space 3}0.000{col 58}{space 4} .0499101{col 71}{space 3}  .110991
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.033125{col 30}{space 2} .0048963{col 41}{space 1}   -6.77{col 50}{space 3}0.000{col 58}{space 4}-.0427215{col 71}{space 3}-.0235285
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1517355{col 30}{space 2} .0557719{col 41}{space 1}    2.72{col 50}{space 3}0.007{col 58}{space 4} .0424246{col 71}{space 3} .2610465
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0056076{col 30}{space 2} .0010129{col 41}{space 1}    5.54{col 50}{space 3}0.000{col 58}{space 4} .0036224{col 71}{space 3} .0075929
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3824949{col 30}{space 2} .0388428{col 41}{space 1}    9.85{col 50}{space 3}0.000{col 58}{space 4} .3063645{col 71}{space 3} .4586254
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2506166{col 30}{space 2} .0312124{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .1894415{col 71}{space 3} .3117918
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0179816{col 30}{space 2} .0424904{col 41}{space 1}    0.42{col 50}{space 3}0.672{col 58}{space 4}-.0652981{col 71}{space 3} .1012613
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .188271{col 30}{space 2} .0440583{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .1019182{col 71}{space 3} .2746237
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0792093{col 30}{space 2}  .049071{col 41}{space 1}    1.61{col 50}{space 3}0.106{col 58}{space 4}-.0169681{col 71}{space 3} .1753867
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2464576{col 30}{space 2} .0542456{col 41}{space 1}    4.54{col 50}{space 3}0.000{col 58}{space 4} .1401381{col 71}{space 3} .3527771
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3203803{col 30}{space 2} .0445037{col 41}{space 1}    7.20{col 50}{space 3}0.000{col 58}{space 4} .2331548{col 71}{space 3} .4076059
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0075399{col 30}{space 2} .0506193{col 41}{space 1}    0.15{col 50}{space 3}0.882{col 58}{space 4}-.0916722{col 71}{space 3} .1067519
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0160357{col 30}{space 2}   .01054{col 41}{space 1}   -1.52{col 50}{space 3}0.128{col 58}{space 4}-.0366937{col 71}{space 3} .0046223
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .377906{col 30}{space 2} .0581708{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .2638933{col 71}{space 3} .4919186
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0909279{col 30}{space 2} .0569364{col 41}{space 1}    1.60{col 50}{space 3}0.110{col 58}{space 4}-.0206654{col 71}{space 3} .2025211
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8666771{col 30}{space 2} .0644892{col 41}{space 1}   13.44{col 50}{space 3}0.000{col 58}{space 4} .7402807{col 71}{space 3} .9930735
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7942385{col 30}{space 2} .0611116{col 41}{space 1}   13.00{col 50}{space 3}0.000{col 58}{space 4}  .674462{col 71}{space 3}  .914015
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1218305{col 30}{space 2} .0702521{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4} -.015861{col 71}{space 3} .2595221
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0786321{col 30}{space 2} .0565425{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-.1894535{col 71}{space 3} .0321892
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0280701{col 30}{space 2} .0199517{col 41}{space 1}   -1.41{col 50}{space 3}0.159{col 58}{space 4}-.0671746{col 71}{space 3} .0110344
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5409084{col 30}{space 2} .0334239{col 41}{space 1}  -16.18{col 50}{space 3}0.000{col 58}{space 4}-.6064181{col 71}{space 3}-.4753987
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4956429{col 30}{space 2} .0339895{col 41}{space 1}  -14.58{col 50}{space 3}0.000{col 58}{space 4}-.5622611{col 71}{space 3}-.4290246
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3543799{col 30}{space 2} .0333067{col 41}{space 1}  -10.64{col 50}{space 3}0.000{col 58}{space 4}-.4196598{col 71}{space 3}   -.2891
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23376.706}  
Iteration 1:{space 3}log pseudolikelihood = {res:-23376.706}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   2135.87
{txt}Log pseudolikelihood = {res}-23376.706{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0335942{col 30}{space 2} .0024244{col 41}{space 1}   13.86{col 50}{space 3}0.000{col 58}{space 4} .0288425{col 71}{space 3} .0383459
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0019656{col 30}{space 2} .0010306{col 41}{space 1}   -1.91{col 50}{space 3}0.056{col 58}{space 4}-.0039855{col 71}{space 3} .0000543
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0067793{col 30}{space 2} .0121375{col 41}{space 1}   -0.56{col 50}{space 3}0.576{col 58}{space 4}-.0305683{col 71}{space 3} .0170096
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0002579{col 30}{space 2} .0001923{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.0006347{col 71}{space 3}  .000119
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0110227{col 30}{space 2} .0067352{col 41}{space 1}    1.64{col 50}{space 3}0.102{col 58}{space 4}-.0021781{col 71}{space 3} .0242235
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .055528{col 30}{space 2} .0066957{col 41}{space 1}    8.29{col 50}{space 3}0.000{col 58}{space 4} .0424046{col 71}{space 3} .0686514
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0392464{col 30}{space 2} .0133665{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .0130486{col 71}{space 3} .0654442
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0462497{col 30}{space 2} .0087937{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4} .0290144{col 71}{space 3}  .063485
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0054538{col 30}{space 2} .0092926{col 41}{space 1}    0.59{col 50}{space 3}0.557{col 58}{space 4}-.0127593{col 71}{space 3}  .023667
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0209734{col 30}{space 2} .0067844{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .0076762{col 71}{space 3} .0342706
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0381114{col 30}{space 2} .0070659{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .0242626{col 71}{space 3} .0519603
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0381155{col 30}{space 2} .0062434{col 41}{space 1}   -6.10{col 50}{space 3}0.000{col 58}{space 4}-.0503523{col 71}{space 3}-.0258787
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0007856{col 30}{space 2}  .000719{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4}-.0021947{col 71}{space 3} .0006236
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0100929{col 30}{space 2} .0060047{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0016761{col 71}{space 3} .0218619
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0412062{col 30}{space 2} .0176175{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0066765{col 71}{space 3} .0757358
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0900923{col 30}{space 2} .0120793{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4} .0664174{col 71}{space 3} .1137672
{txt}electricity_mean {c |}{col 18}{res}{space 2}   .10392{col 30}{space 2} .0123402{col 41}{space 1}    8.42{col 50}{space 3}0.000{col 58}{space 4} .0797338{col 71}{space 3} .1281063
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0033628{col 30}{space 2} .0097236{col 41}{space 1}    0.35{col 50}{space 3}0.729{col 58}{space 4}-.0156952{col 71}{space 3} .0224208
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0471515{col 30}{space 2} .0099741{col 41}{space 1}    4.73{col 50}{space 3}0.000{col 58}{space 4} .0276025{col 71}{space 3} .0667004
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.0195625{col 30}{space 2} .0029935{col 41}{space 1}   -6.53{col 50}{space 3}0.000{col 58}{space 4}-.0254296{col 71}{space 3}-.0136953
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0115762{col 30}{space 2}  .007019{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0021808{col 71}{space 3} .0253332
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0210902{col 30}{space 2} .0058595{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0096057{col 71}{space 3} .0325747
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0022034{col 30}{space 2} .0061757{col 41}{space 1}    0.36{col 50}{space 3}0.721{col 58}{space 4}-.0099007{col 71}{space 3} .0143075
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.505946{col 30}{space 2} .0153761{col 41}{space 1}   97.94{col 50}{space 3}0.000{col 58}{space 4}  1.47581{col 71}{space 3} 1.536083
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1922052{col 30}{space 2}  .013825{col 41}{space 1}   13.90{col 50}{space 3}0.000{col 58}{space 4} .1651088{col 71}{space 3} .2193017
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0112458{col 30}{space 2} .0058973{col 41}{space 1}   -1.91{col 50}{space 3}0.057{col 58}{space 4}-.0228043{col 71}{space 3} .0003126
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0387872{col 30}{space 2} .0694464{col 41}{space 1}   -0.56{col 50}{space 3}0.576{col 58}{space 4}-.1748998{col 71}{space 3} .0973253
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014754{col 30}{space 2} .0010998{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4} -.003631{col 71}{space 3} .0006803
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0630651{col 30}{space 2} .0385393{col 41}{space 1}    1.64{col 50}{space 3}0.102{col 58}{space 4}-.0124705{col 71}{space 3} .1386008
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3176971{col 30}{space 2} .0383258{col 41}{space 1}    8.29{col 50}{space 3}0.000{col 58}{space 4} .2425799{col 71}{space 3} .3928144
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2245438{col 30}{space 2} .0764697{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .0746658{col 71}{space 3} .3744217
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2646124{col 30}{space 2} .0503108{col 41}{space 1}    5.26{col 50}{space 3}0.000{col 58}{space 4} .1660052{col 71}{space 3} .3632197
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0312035{col 30}{space 2} .0531651{col 41}{space 1}    0.59{col 50}{space 3}0.557{col 58}{space 4}-.0729983{col 71}{space 3} .1354053
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1199969{col 30}{space 2} .0388114{col 41}{space 1}    3.09{col 50}{space 3}0.002{col 58}{space 4} .0439279{col 71}{space 3} .1960659
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2180502{col 30}{space 2} .0404341{col 41}{space 1}    5.39{col 50}{space 3}0.000{col 58}{space 4} .1388009{col 71}{space 3} .2972996
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2180736{col 30}{space 2} .0357184{col 41}{space 1}   -6.11{col 50}{space 3}0.000{col 58}{space 4}-.2880804{col 71}{space 3}-.1480668
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0044946{col 30}{space 2} .0041134{col 41}{space 1}   -1.09{col 50}{space 3}0.275{col 58}{space 4}-.0125567{col 71}{space 3} .0035675
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0577455{col 30}{space 2} .0343581{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4}-.0095951{col 71}{space 3}  .125086
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2357564{col 30}{space 2} .1008045{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0381832{col 71}{space 3} .4333296
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5154527{col 30}{space 2} .0691113{col 41}{space 1}    7.46{col 50}{space 3}0.000{col 58}{space 4}  .379997{col 71}{space 3} .6509085
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5945667{col 30}{space 2} .0705596{col 41}{space 1}    8.43{col 50}{space 3}0.000{col 58}{space 4} .4562725{col 71}{space 3}  .732861
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0192399{col 30}{space 2} .0556335{col 41}{space 1}    0.35{col 50}{space 3}0.729{col 58}{space 4}-.0897997{col 71}{space 3} .1282796
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2697717{col 30}{space 2} .0570381{col 41}{space 1}    4.73{col 50}{space 3}0.000{col 58}{space 4} .1579791{col 71}{space 3} .3815643
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2}-.1119246{col 30}{space 2} .0171103{col 41}{space 1}   -6.54{col 50}{space 3}0.000{col 58}{space 4}-.1454601{col 71}{space 3}-.0783891
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0662319{col 30}{space 2} .0401699{col 41}{space 1}    1.65{col 50}{space 3}0.099{col 58}{space 4}-.0124995{col 71}{space 3} .1449634
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  .120665{col 30}{space 2} .0335209{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0549653{col 71}{space 3} .1863647
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0126064{col 30}{space 2} .0353313{col 41}{space 1}    0.36{col 50}{space 3}0.721{col 58}{space 4}-.0566417{col 71}{space 3} .0818545
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9  pdd9   $xlist  pdd9_mean  $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-31895.416}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31895.416}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 49}Wald chi2({res}25{txt}){col 67}= {res}   2401.78
{txt}Log pseudolikelihood = {res}-31895.416{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .0179502{col 30}{space 2}  .002041{col 41}{space 1}    8.79{col 50}{space 3}0.000{col 58}{space 4} .0139499{col 71}{space 3} .0219504
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0013981{col 30}{space 2} .0010129{col 41}{space 1}    1.38{col 50}{space 3}0.167{col 58}{space 4}-.0005872{col 71}{space 3} .0033834
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0075029{col 30}{space 2} .0116241{col 41}{space 1}    0.65{col 50}{space 3}0.519{col 58}{space 4}-.0152799{col 71}{space 3} .0302856
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003738{col 30}{space 2} .0001919{col 41}{space 1}   -1.95{col 50}{space 3}0.051{col 58}{space 4}-.0007499{col 71}{space 3} 2.27e-06
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0102504{col 30}{space 2} .0064678{col 41}{space 1}    1.58{col 50}{space 3}0.113{col 58}{space 4}-.0024263{col 71}{space 3} .0229271
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0721549{col 30}{space 2} .0065919{col 41}{space 1}   10.95{col 50}{space 3}0.000{col 58}{space 4}  .059235{col 71}{space 3} .0850748
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0343613{col 30}{space 2} .0091238{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4}  .016479{col 71}{space 3} .0522436
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .045813{col 30}{space 2} .0069908{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4} .0321112{col 71}{space 3} .0595148
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0566588{col 30}{space 2} .0064539{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .0440094{col 71}{space 3} .0693082
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .007546{col 30}{space 2} .0054534{col 41}{space 1}    1.38{col 50}{space 3}0.166{col 58}{space 4}-.0031425{col 71}{space 3} .0182344
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0353338{col 30}{space 2} .0056905{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4} .0241807{col 71}{space 3}  .046487
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.014005{col 30}{space 2} .0049696{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.0237452{col 71}{space 3}-.0042649
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0002577{col 30}{space 2} .0003482{col 41}{space 1}    0.74{col 50}{space 3}0.459{col 58}{space 4}-.0004248{col 71}{space 3} .0009401
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0006422{col 30}{space 2} .0054247{col 41}{space 1}    0.12{col 50}{space 3}0.906{col 58}{space 4}  -.00999{col 71}{space 3} .0112745
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0160401{col 30}{space 2} .0141534{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4}   -.0117{col 71}{space 3} .0437803
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0661889{col 30}{space 2}  .011681{col 41}{space 1}    5.67{col 50}{space 3}0.000{col 58}{space 4} .0432946{col 71}{space 3} .0890833
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0697138{col 30}{space 2} .0117733{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0466387{col 71}{space 3}  .092789
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0287063{col 30}{space 2} .0099978{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4}  .009111{col 71}{space 3} .0483017
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0604631{col 30}{space 2} .0096934{col 41}{space 1}    6.24{col 50}{space 3}0.000{col 58}{space 4} .0414645{col 71}{space 3} .0794618
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0067694{col 30}{space 2} .0031007{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0006921{col 71}{space 3} .0128468
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} -.026337{col 30}{space 2} .0074985{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.0410339{col 71}{space 3}-.0116402
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0152452{col 30}{space 2} .0063267{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.0276454{col 71}{space 3}-.0028451
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0608317{col 30}{space 2} .0060424{col 41}{space 1}   10.07{col 50}{space 3}0.000{col 58}{space 4} .0489889{col 71}{space 3} .0726745
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0161876{col 30}{space 2} .0062104{col 41}{space 1}    2.61{col 50}{space 3}0.009{col 58}{space 4} .0040153{col 71}{space 3} .0283598
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0521257{col 30}{space 2} .0057207{col 41}{space 1}    9.11{col 50}{space 3}0.000{col 58}{space 4} .0409132{col 71}{space 3} .0633381
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  1.40973{col 30}{space 2} .0166367{col 41}{space 1}   84.74{col 50}{space 3}0.000{col 58}{space 4} 1.377122{col 71}{space 3} 1.442337
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9 hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 12}pdd9 {c |}{col 18}{res}{space 2} .1003288{col 30}{space 2} .0114002{col 41}{space 1}    8.80{col 50}{space 3}0.000{col 58}{space 4} .0779849{col 71}{space 3} .1226727
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0078145{col 30}{space 2}  .005662{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0032829{col 71}{space 3} .0189118
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0419358{col 30}{space 2} .0649685{col 41}{space 1}    0.65{col 50}{space 3}0.519{col 58}{space 4}-.0854001{col 71}{space 3} .1692716
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0020892{col 30}{space 2} .0010725{col 41}{space 1}   -1.95{col 50}{space 3}0.051{col 58}{space 4}-.0041913{col 71}{space 3} .0000128
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0572926{col 30}{space 2} .0361496{col 41}{space 1}    1.58{col 50}{space 3}0.113{col 58}{space 4}-.0135593{col 71}{space 3} .1281445
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .4032954{col 30}{space 2} .0368081{col 41}{space 1}   10.96{col 50}{space 3}0.000{col 58}{space 4} .3311529{col 71}{space 3}  .475438
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1920557{col 30}{space 2} .0509862{col 41}{space 1}    3.77{col 50}{space 3}0.000{col 58}{space 4} .0921246{col 71}{space 3} .2919868
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2560626{col 30}{space 2} .0390497{col 41}{space 1}    6.56{col 50}{space 3}0.000{col 58}{space 4} .1795266{col 71}{space 3} .3325985
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3166831{col 30}{space 2} .0360663{col 41}{space 1}    8.78{col 50}{space 3}0.000{col 58}{space 4} .2459945{col 71}{space 3} .3873716
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0421766{col 30}{space 2} .0304843{col 41}{space 1}    1.38{col 50}{space 3}0.166{col 58}{space 4}-.0175714{col 71}{space 3} .1019247
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .1974915{col 30}{space 2} .0318148{col 41}{space 1}    6.21{col 50}{space 3}0.000{col 58}{space 4} .1351357{col 71}{space 3} .2598473
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0782783{col 30}{space 2} .0277772{col 41}{space 1}   -2.82{col 50}{space 3}0.005{col 58}{space 4}-.1327206{col 71}{space 3} -.023836
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0014401{col 30}{space 2} .0019464{col 41}{space 1}    0.74{col 50}{space 3}0.459{col 58}{space 4}-.0023747{col 71}{space 3} .0052549
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0035897{col 30}{space 2} .0303206{col 41}{space 1}    0.12{col 50}{space 3}0.906{col 58}{space 4}-.0558376{col 71}{space 3}  .063017
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0896531{col 30}{space 2} .0791105{col 41}{space 1}    1.13{col 50}{space 3}0.257{col 58}{space 4}-.0654007{col 71}{space 3} .2447069
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .36995{col 30}{space 2} .0652375{col 41}{space 1}    5.67{col 50}{space 3}0.000{col 58}{space 4} .2420868{col 71}{space 3} .4978132
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3896516{col 30}{space 2} .0657483{col 41}{space 1}    5.93{col 50}{space 3}0.000{col 58}{space 4} .2607873{col 71}{space 3} .5185159
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1604483{col 30}{space 2} .0558923{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0509015{col 71}{space 3} .2699951
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3379467{col 30}{space 2} .0541908{col 41}{space 1}    6.24{col 50}{space 3}0.000{col 58}{space 4} .2317346{col 71}{space 3} .4441587
{txt}{space 7}pdd9_mean {c |}{col 18}{res}{space 2} .0378363{col 30}{space 2} .0173248{col 41}{space 1}    2.18{col 50}{space 3}0.029{col 58}{space 4} .0038803{col 71}{space 3} .0717923
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1472056{col 30}{space 2} .0418878{col 41}{space 1}   -3.51{col 50}{space 3}0.000{col 58}{space 4}-.2293041{col 71}{space 3}-.0651071
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0852102{col 30}{space 2} .0353683{col 41}{space 1}   -2.41{col 50}{space 3}0.016{col 58}{space 4}-.1545308{col 71}{space 3}-.0158897
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3400068{col 30}{space 2} .0337514{col 41}{space 1}   10.07{col 50}{space 3}0.000{col 58}{space 4} .2738552{col 71}{space 3} .4061583
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0904772{col 30}{space 2} .0347101{col 41}{space 1}    2.61{col 50}{space 3}0.009{col 58}{space 4} .0224466{col 71}{space 3} .1585078
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2}  .291346{col 30}{space 2} .0319949{col 41}{space 1}    9.11{col 50}{space 3}0.000{col 58}{space 4} .2286372{col 71}{space 3} .3540548
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S24_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9   $xlist  pdd9_mean   )
{res}{txt}(note: file S24_poisson.rtf not found)
(output written to {browse  `"S24_poisson.rtf"'})

{com}. 
. 
. 
. 
. ********************************************************************************
. *                                   S25                                        *
. ********************************************************************************
. *                          vill_village_level                                  *
. 
. eststo clear
{txt}
{com}. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-128723.42}  
Iteration 1:{space 3}log pseudolikelihood = {res:-128723.41}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 49}Wald chi2({res}36{txt}){col 67}= {res}  18895.72
{txt}Log pseudolikelihood = {res}-128723.41{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0086879{col 30}{space 2} .0013158{col 41}{space 1}    6.60{col 50}{space 3}0.000{col 58}{space 4}  .006109{col 71}{space 3} .0112667
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0097154{col 30}{space 2} .0004577{col 41}{space 1}  -21.23{col 50}{space 3}0.000{col 58}{space 4}-.0106125{col 71}{space 3}-.0088183
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0003256{col 30}{space 2} .0004522{col 41}{space 1}    0.72{col 50}{space 3}0.472{col 58}{space 4}-.0005608{col 71}{space 3} .0012119
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .003965{col 30}{space 2} .0053936{col 41}{space 1}    0.74{col 50}{space 3}0.462{col 58}{space 4}-.0066063{col 71}{space 3} .0145362
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0000152{col 30}{space 2} .0000883{col 41}{space 1}   -0.17{col 50}{space 3}0.863{col 58}{space 4}-.0001883{col 71}{space 3} .0001579
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0085868{col 30}{space 2} .0032463{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0022241{col 71}{space 3} .0149494
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0639865{col 30}{space 2} .0029088{col 41}{space 1}   22.00{col 50}{space 3}0.000{col 58}{space 4} .0582855{col 71}{space 3} .0696876
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0200996{col 30}{space 2} .0049695{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .0103594{col 71}{space 3} .0298397
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0338631{col 30}{space 2} .0037117{col 41}{space 1}    9.12{col 50}{space 3}0.000{col 58}{space 4} .0265883{col 71}{space 3} .0411379
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0247387{col 30}{space 2} .0040499{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4} .0168011{col 71}{space 3} .0326763
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0229707{col 30}{space 2} .0035291{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .0160538{col 71}{space 3} .0298877
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0388896{col 30}{space 2}  .003318{col 41}{space 1}   11.72{col 50}{space 3}0.000{col 58}{space 4} .0323865{col 71}{space 3} .0453926
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0158382{col 30}{space 2} .0028549{col 41}{space 1}   -5.55{col 50}{space 3}0.000{col 58}{space 4}-.0214337{col 71}{space 3}-.0102427
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .000013{col 30}{space 2} .0002064{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.0003916{col 71}{space 3} .0004177
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0345312{col 30}{space 2}   .00314{col 41}{space 1}   11.00{col 50}{space 3}0.000{col 58}{space 4}  .028377{col 71}{space 3} .0406854
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0026207{col 30}{space 2} .0066133{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4} -.010341{col 71}{space 3} .0155825
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1040504{col 30}{space 2} .0053941{col 41}{space 1}   19.29{col 50}{space 3}0.000{col 58}{space 4} .0934782{col 71}{space 3} .1146226
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1022415{col 30}{space 2} .0054644{col 41}{space 1}   18.71{col 50}{space 3}0.000{col 58}{space 4} .0915315{col 71}{space 3} .1129515
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0148452{col 30}{space 2} .0051831{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0046865{col 71}{space 3} .0250039
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0238282{col 30}{space 2}  .004654{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4} .0147065{col 71}{space 3} .0329499
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0182796{col 30}{space 2} .0016932{col 41}{space 1}   10.80{col 50}{space 3}0.000{col 58}{space 4}  .014961{col 71}{space 3} .0215982
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.1262881{col 30}{space 2} .0060283{col 41}{space 1}  -20.95{col 50}{space 3}0.000{col 58}{space 4}-.1381032{col 71}{space 3}-.1144729
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.3742055{col 30}{space 2} .0067333{col 41}{space 1}  -55.58{col 50}{space 3}0.000{col 58}{space 4}-.3874026{col 71}{space 3}-.3610084
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.1591354{col 30}{space 2} .0063889{col 41}{space 1}  -24.91{col 50}{space 3}0.000{col 58}{space 4}-.1716574{col 71}{space 3}-.1466133
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.1440439{col 30}{space 2} .0066333{col 41}{space 1}  -21.72{col 50}{space 3}0.000{col 58}{space 4} -.157045{col 71}{space 3}-.1310428
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .0162335{col 30}{space 2} .0073893{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0017508{col 71}{space 3} .0307163
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0517214{col 30}{space 2} .0089446{col 41}{space 1}   -5.78{col 50}{space 3}0.000{col 58}{space 4}-.0692526{col 71}{space 3}-.0341903
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0071583{col 30}{space 2}  .006587{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.0057519{col 71}{space 3} .0200686
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0024319{col 30}{space 2} .0074232{col 41}{space 1}   -0.33{col 50}{space 3}0.743{col 58}{space 4} -.016981{col 71}{space 3} .0121172
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0062736{col 30}{space 2} .0066498{col 41}{space 1}    0.94{col 50}{space 3}0.345{col 58}{space 4}-.0067598{col 71}{space 3} .0193071
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0196925{col 30}{space 2} .0074281{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0051338{col 71}{space 3} .0342512
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0235797{col 30}{space 2}  .007437{col 41}{space 1}   -3.17{col 50}{space 3}0.002{col 58}{space 4} -.038156{col 71}{space 3}-.0090034
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0332108{col 30}{space 2} .0071424{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4} .0192121{col 71}{space 3} .0472096
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0463158{col 30}{space 2} .0105309{col 41}{space 1}   -4.40{col 50}{space 3}0.000{col 58}{space 4}-.0669559{col 71}{space 3}-.0256756
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0782844{col 30}{space 2} .0073666{col 41}{space 1}   10.63{col 50}{space 3}0.000{col 58}{space 4} .0638461{col 71}{space 3} .0927227
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0123993{col 30}{space 2} .0072891{col 41}{space 1}   -1.70{col 50}{space 3}0.089{col 58}{space 4}-.0266856{col 71}{space 3} .0018869
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.561323{col 30}{space 2} .0113326{col 41}{space 1}  137.77{col 50}{space 3}0.000{col 58}{space 4} 1.539112{col 71}{space 3} 1.583535
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0474358{col 30}{space 2} .0071831{col 41}{space 1}    6.60{col 50}{space 3}0.000{col 58}{space 4} .0333573{col 71}{space 3} .0615143
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0530459{col 30}{space 2} .0024968{col 41}{space 1}  -21.25{col 50}{space 3}0.000{col 58}{space 4}-.0579396{col 71}{space 3}-.0481522
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0017776{col 30}{space 2} .0024691{col 41}{space 1}    0.72{col 50}{space 3}0.472{col 58}{space 4}-.0030617{col 71}{space 3} .0066169
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0216487{col 30}{space 2} .0294485{col 41}{space 1}    0.74{col 50}{space 3}0.462{col 58}{space 4}-.0360692{col 71}{space 3} .0793666
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0000831{col 30}{space 2} .0004822{col 41}{space 1}   -0.17{col 50}{space 3}0.863{col 58}{space 4}-.0010282{col 71}{space 3}  .000862
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0468836{col 30}{space 2} .0177256{col 41}{space 1}    2.64{col 50}{space 3}0.008{col 58}{space 4}  .012142{col 71}{space 3} .0816252
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3493662{col 30}{space 2} .0158811{col 41}{space 1}   22.00{col 50}{space 3}0.000{col 58}{space 4} .3182399{col 71}{space 3} .3804926
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1097435{col 30}{space 2} .0271333{col 41}{space 1}    4.04{col 50}{space 3}0.000{col 58}{space 4} .0565633{col 71}{space 3} .1629237
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1848923{col 30}{space 2} .0202628{col 41}{space 1}    9.12{col 50}{space 3}0.000{col 58}{space 4} .1451779{col 71}{space 3} .2246066
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1350731{col 30}{space 2} .0221114{col 41}{space 1}    6.11{col 50}{space 3}0.000{col 58}{space 4} .0917355{col 71}{space 3} .1784107
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1254202{col 30}{space 2} .0192695{col 41}{space 1}    6.51{col 50}{space 3}0.000{col 58}{space 4} .0876526{col 71}{space 3} .1631877
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2123368{col 30}{space 2} .0181168{col 41}{space 1}   11.72{col 50}{space 3}0.000{col 58}{space 4} .1768286{col 71}{space 3}  .247845
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0864767{col 30}{space 2} .0155881{col 41}{space 1}   -5.55{col 50}{space 3}0.000{col 58}{space 4}-.1170288{col 71}{space 3}-.0559247
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0000712{col 30}{space 2} .0011272{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4} -.002138{col 71}{space 3} .0022805
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1885402{col 30}{space 2} .0171446{col 41}{space 1}   11.00{col 50}{space 3}0.000{col 58}{space 4} .1549375{col 71}{space 3} .2221429
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0143093{col 30}{space 2} .0361083{col 41}{space 1}    0.40{col 50}{space 3}0.692{col 58}{space 4}-.0564618{col 71}{space 3} .0850803
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5681148{col 30}{space 2} .0294379{col 41}{space 1}   19.30{col 50}{space 3}0.000{col 58}{space 4} .5104176{col 71}{space 3} .6258121
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5582382{col 30}{space 2} .0298195{col 41}{space 1}   18.72{col 50}{space 3}0.000{col 58}{space 4} .4997931{col 71}{space 3} .6166833
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0810548{col 30}{space 2} .0283005{col 41}{space 1}    2.86{col 50}{space 3}0.004{col 58}{space 4} .0255868{col 71}{space 3} .1365228
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1301018{col 30}{space 2} .0254096{col 41}{space 1}    5.12{col 50}{space 3}0.000{col 58}{space 4}    .0803{col 71}{space 3} .1799037
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0998066{col 30}{space 2} .0092434{col 41}{space 1}   10.80{col 50}{space 3}0.000{col 58}{space 4} .0816899{col 71}{space 3} .1179234
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.7550257{col 30}{space 2} .0370758{col 41}{space 1}  -20.36{col 50}{space 3}0.000{col 58}{space 4} -.827693{col 71}{space 3}-.6823583
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.986632{col 30}{space 2} .0379443{col 41}{space 1}  -52.36{col 50}{space 3}0.000{col 58}{space 4}-2.061001{col 71}{space 3}-1.912262
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2} -.936274{col 30}{space 2}  .038916{col 41}{space 1}  -24.06{col 50}{space 3}0.000{col 58}{space 4}-1.012548{col 71}{space 3}-.8600001
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.8537395{col 30}{space 2} .0402886{col 41}{space 1}  -21.19{col 50}{space 3}0.000{col 58}{space 4}-.9327037{col 71}{space 3}-.7747753
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .1041542{col 30}{space 2} .0474125{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .0112275{col 71}{space 3}  .197081
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2722459{col 30}{space 2}  .047177{col 41}{space 1}   -5.77{col 50}{space 3}0.000{col 58}{space 4}-.3647111{col 71}{space 3}-.1797808
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} .0388009{col 30}{space 2} .0356048{col 41}{space 1}    1.09{col 50}{space 3}0.276{col 58}{space 4}-.0309833{col 71}{space 3} .1085851
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0131186{col 30}{space 2} .0400711{col 41}{space 1}   -0.33{col 50}{space 3}0.743{col 58}{space 4}-.0916565{col 71}{space 3} .0654194
{txt}{space 11}2012  {c |}{col 18}{res}{space 2} .0339903{col 30}{space 2} .0359524{col 41}{space 1}    0.95{col 50}{space 3}0.344{col 58}{space 4}-.0364752{col 71}{space 3} .1044558
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .1074133{col 30}{space 2} .0402964{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0284339{col 71}{space 3} .1863928
{txt}{space 11}2014  {c |}{col 18}{res}{space 2} -.125864{col 30}{space 2} .0399107{col 41}{space 1}   -3.15{col 50}{space 3}0.002{col 58}{space 4}-.2040875{col 71}{space 3}-.0476405
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1823834{col 30}{space 2} .0387944{col 41}{space 1}    4.70{col 50}{space 3}0.000{col 58}{space 4} .1063478{col 71}{space 3}  .258419
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2444466{col 30}{space 2}   .05529{col 41}{space 1}   -4.42{col 50}{space 3}0.000{col 58}{space 4} -.352813{col 71}{space 3}-.1360803
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .4398041{col 30}{space 2} .0405166{col 41}{space 1}   10.85{col 50}{space 3}0.000{col 58}{space 4}  .360393{col 71}{space 3} .5192152
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0665554{col 30}{space 2} .0392556{col 41}{space 1}   -1.70{col 50}{space 3}0.090{col 58}{space 4} -.143495{col 71}{space 3} .0103843
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-20894.272}  
Iteration 1:{space 3}log pseudolikelihood = {res:-20894.272}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   2603.39
{txt}Log pseudolikelihood = {res}-20894.272{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0123987{col 30}{space 2} .0035966{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0053496{col 71}{space 3} .0194479
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.014787{col 30}{space 2} .0018957{col 41}{space 1}   -7.80{col 50}{space 3}0.000{col 58}{space 4}-.0185024{col 71}{space 3}-.0110715
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0122032{col 30}{space 2}  .001704{col 41}{space 1}    7.16{col 50}{space 3}0.000{col 58}{space 4} .0088635{col 71}{space 3}  .015543
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.010461{col 30}{space 2} .0147884{col 41}{space 1}   -0.71{col 50}{space 3}0.479{col 58}{space 4}-.0394457{col 71}{space 3} .0185236
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0010991{col 30}{space 2} .0002456{col 41}{space 1}   -4.47{col 50}{space 3}0.000{col 58}{space 4}-.0015806{col 71}{space 3}-.0006177
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0090051{col 30}{space 2} .0089211{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.0264901{col 71}{space 3} .0084799
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0912026{col 30}{space 2} .0076079{col 41}{space 1}   11.99{col 50}{space 3}0.000{col 58}{space 4} .0762914{col 71}{space 3} .1061138
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0459809{col 30}{space 2} .0320259{col 41}{space 1}   -1.44{col 50}{space 3}0.151{col 58}{space 4}-.1087504{col 71}{space 3} .0167887
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0435593{col 30}{space 2} .0089701{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .0259781{col 71}{space 3} .0611404
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0417576{col 30}{space 2} .0107407{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4} .0207063{col 71}{space 3} .0628089
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0149892{col 30}{space 2} .0132868{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0110525{col 71}{space 3} .0410309
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0509823{col 30}{space 2} .0115014{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4}   .02844{col 71}{space 3} .0735245
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0447756{col 30}{space 2} .0078912{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.0602421{col 71}{space 3} -.029309
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}  .003529{col 30}{space 2} .0008232{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .0019156{col 71}{space 3} .0051425
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0752747{col 30}{space 2} .0076616{col 41}{space 1}    9.82{col 50}{space 3}0.000{col 58}{space 4} .0602582{col 71}{space 3} .0902911
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1849037{col 30}{space 2} .0498666{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .0871671{col 71}{space 3} .2826404
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1056696{col 30}{space 2} .0133591{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .0794863{col 71}{space 3} .1318529
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0658322{col 30}{space 2} .0158594{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0347483{col 71}{space 3} .0969161
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0902029{col 30}{space 2}  .020128{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4} .0507527{col 71}{space 3}  .129653
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0126535{col 30}{space 2} .0145011{col 41}{space 1}    0.87{col 50}{space 3}0.383{col 58}{space 4}-.0157681{col 71}{space 3}  .041075
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0215486{col 30}{space 2} .0043433{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0130359{col 71}{space 3} .0300613
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0300508{col 30}{space 2} .0053906{col 41}{space 1}   -5.57{col 50}{space 3}0.000{col 58}{space 4}-.0406162{col 71}{space 3}-.0194854
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.185807{col 30}{space 2}  .024377{col 41}{space 1}   48.64{col 50}{space 3}0.000{col 58}{space 4} 1.138029{col 71}{space 3} 1.233585
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0524485{col 30}{space 2} .0152151{col 41}{space 1}    3.45{col 50}{space 3}0.001{col 58}{space 4} .0226276{col 71}{space 3} .0822695
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2} -.062551{col 30}{space 2} .0080122{col 41}{space 1}   -7.81{col 50}{space 3}0.000{col 58}{space 4}-.0782546{col 71}{space 3}-.0468475
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0516215{col 30}{space 2} .0072035{col 41}{space 1}    7.17{col 50}{space 3}0.000{col 58}{space 4} .0375028{col 71}{space 3} .0657402
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0442518{col 30}{space 2} .0625547{col 41}{space 1}   -0.71{col 50}{space 3}0.479{col 58}{space 4}-.1668567{col 71}{space 3} .0783531
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0046495{col 30}{space 2} .0010395{col 41}{space 1}   -4.47{col 50}{space 3}0.000{col 58}{space 4}-.0066868{col 71}{space 3}-.0026122
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0380928{col 30}{space 2} .0377353{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.1120528{col 71}{space 3} .0358671
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3858005{col 30}{space 2} .0322188{col 41}{space 1}   11.97{col 50}{space 3}0.000{col 58}{space 4} .3226528{col 71}{space 3} .4489482
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1945059{col 30}{space 2}  .135477{col 41}{space 1}   -1.44{col 50}{space 3}0.151{col 58}{space 4}-.4600359{col 71}{space 3} .0710241
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1842622{col 30}{space 2} .0379492{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .1098831{col 71}{space 3} .2586412
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1766407{col 30}{space 2}  .045425{col 41}{space 1}    3.89{col 50}{space 3}0.000{col 58}{space 4} .0876093{col 71}{space 3} .2656721
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0634066{col 30}{space 2} .0562045{col 41}{space 1}    1.13{col 50}{space 3}0.259{col 58}{space 4}-.0467522{col 71}{space 3} .1735654
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2156627{col 30}{space 2} .0486522{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .1203061{col 71}{space 3} .3110193
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1894073{col 30}{space 2} .0333942{col 41}{space 1}   -5.67{col 50}{space 3}0.000{col 58}{space 4}-.2548587{col 71}{space 3}-.1239558
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0149283{col 30}{space 2}  .003482{col 41}{space 1}    4.29{col 50}{space 3}0.000{col 58}{space 4} .0081036{col 71}{space 3} .0217529
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3184231{col 30}{space 2} .0324455{col 41}{space 1}    9.81{col 50}{space 3}0.000{col 58}{space 4} .2548311{col 71}{space 3} .3820151
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7821703{col 30}{space 2} .2109572{col 41}{space 1}    3.71{col 50}{space 3}0.000{col 58}{space 4} .3687018{col 71}{space 3} 1.195639
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4469981{col 30}{space 2} .0565351{col 41}{space 1}    7.91{col 50}{space 3}0.000{col 58}{space 4} .3361914{col 71}{space 3} .5578048
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2784801{col 30}{space 2} .0671081{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .1469506{col 71}{space 3} .4100096
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3815716{col 30}{space 2} .0850988{col 41}{space 1}    4.48{col 50}{space 3}0.000{col 58}{space 4}  .214781{col 71}{space 3} .5483623
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .053526{col 30}{space 2} .0613387{col 41}{space 1}    0.87{col 50}{space 3}0.383{col 58}{space 4}-.0666956{col 71}{space 3} .1737476
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}  .091154{col 30}{space 2} .0183604{col 41}{space 1}    4.96{col 50}{space 3}0.000{col 58}{space 4} .0551682{col 71}{space 3} .1271398
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1271193{col 30}{space 2}   .02279{col 41}{space 1}   -5.58{col 50}{space 3}0.000{col 58}{space 4} -.171787{col 71}{space 3}-.0824517
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-9226.8916}  
Iteration 1:{space 3}log pseudolikelihood = {res:-9226.8912}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   1568.80
{txt}Log pseudolikelihood = {res}-9226.8912{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0113054{col 30}{space 2} .0042944{col 41}{space 1}    2.63{col 50}{space 3}0.008{col 58}{space 4} .0028886{col 71}{space 3} .0197222
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0085123{col 30}{space 2} .0016502{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0117465{col 71}{space 3} -.005278
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} -.001466{col 30}{space 2} .0020315{col 41}{space 1}   -0.72{col 50}{space 3}0.471{col 58}{space 4}-.0054476{col 71}{space 3} .0025156
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0401348{col 30}{space 2} .0183245{col 41}{space 1}   -2.19{col 50}{space 3}0.029{col 58}{space 4}-.0760503{col 71}{space 3}-.0042194
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}  -.00038{col 30}{space 2} .0003014{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-.0009707{col 71}{space 3} .0002107
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0154511{col 30}{space 2} .0109963{col 41}{space 1}   -1.41{col 50}{space 3}0.160{col 58}{space 4}-.0370034{col 71}{space 3} .0061012
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .062557{col 30}{space 2} .0109969{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .0410034{col 71}{space 3} .0841106
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0354851{col 30}{space 2} .0278303{col 41}{space 1}    1.28{col 50}{space 3}0.202{col 58}{space 4}-.0190614{col 71}{space 3} .0900315
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .017474{col 30}{space 2} .0119882{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0060224{col 71}{space 3} .0409704
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0296056{col 30}{space 2} .0202657{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0101145{col 71}{space 3} .0693257
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0225228{col 30}{space 2} .0133028{col 41}{space 1}    1.69{col 50}{space 3}0.090{col 58}{space 4}-.0035503{col 71}{space 3} .0485958
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0417532{col 30}{space 2} .0093449{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .0234375{col 71}{space 3}  .060069
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0246366{col 30}{space 2} .0079622{col 41}{space 1}   -3.09{col 50}{space 3}0.002{col 58}{space 4}-.0402422{col 71}{space 3} -.009031
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0215698{col 30}{space 2} .0054369{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .0109137{col 71}{space 3}  .032226
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0126817{col 30}{space 2} .0112734{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.0094138{col 71}{space 3} .0347773
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0278538{col 30}{space 2} .0513154{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.0727225{col 71}{space 3} .1284301
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1188737{col 30}{space 2} .0187464{col 41}{space 1}    6.34{col 50}{space 3}0.000{col 58}{space 4} .0821316{col 71}{space 3} .1556159
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0929927{col 30}{space 2}  .025874{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} .0422805{col 71}{space 3} .1437049
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0376325{col 30}{space 2} .0186267{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0011249{col 71}{space 3}   .07414
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0380991{col 30}{space 2} .0164817{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .0057955{col 71}{space 3} .0704027
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0038831{col 30}{space 2} .0064763{col 41}{space 1}   -0.60{col 50}{space 3}0.549{col 58}{space 4}-.0165764{col 71}{space 3} .0088103
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0610642{col 30}{space 2} .0104032{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .0406744{col 71}{space 3}  .081454
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0207003{col 30}{space 2} .0085457{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4}  .003951{col 71}{space 3} .0374496
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.682643{col 30}{space 2} .0355931{col 41}{space 1}   47.27{col 50}{space 3}0.000{col 58}{space 4} 1.612881{col 71}{space 3} 1.752404
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0674095{col 30}{space 2} .0255963{col 41}{space 1}    2.63{col 50}{space 3}0.008{col 58}{space 4} .0172417{col 71}{space 3} .1175773
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0507553{col 30}{space 2}  .009835{col 41}{space 1}   -5.16{col 50}{space 3}0.000{col 58}{space 4}-.0700316{col 71}{space 3}-.0314789
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0087411{col 30}{space 2} .0121093{col 41}{space 1}   -0.72{col 50}{space 3}0.470{col 58}{space 4}-.0324749{col 71}{space 3} .0149926
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2393082{col 30}{space 2} .1093564{col 41}{space 1}   -2.19{col 50}{space 3}0.029{col 58}{space 4}-.4536427{col 71}{space 3}-.0249736
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0022657{col 30}{space 2} .0017966{col 41}{space 1}   -1.26{col 50}{space 3}0.207{col 58}{space 4}-.0057871{col 71}{space 3} .0012556
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0921286{col 30}{space 2}  .065529{col 41}{space 1}   -1.41{col 50}{space 3}0.160{col 58}{space 4}-.2205632{col 71}{space 3}  .036306
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3730025{col 30}{space 2} .0655439{col 41}{space 1}    5.69{col 50}{space 3}0.000{col 58}{space 4} .2445389{col 71}{space 3} .5014661
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2115834{col 30}{space 2} .1659674{col 41}{space 1}    1.27{col 50}{space 3}0.202{col 58}{space 4}-.1137068{col 71}{space 3} .5368736
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1041904{col 30}{space 2} .0714712{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0358905{col 71}{space 3} .2442713
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1765262{col 30}{space 2} .1208086{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0602544{col 71}{space 3} .4133068
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1342942{col 30}{space 2} .0793387{col 41}{space 1}    1.69{col 50}{space 3}0.091{col 58}{space 4}-.0212067{col 71}{space 3} .2897952
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .248958{col 30}{space 2} .0556618{col 41}{space 1}    4.47{col 50}{space 3}0.000{col 58}{space 4} .1398629{col 71}{space 3} .3580532
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1468983{col 30}{space 2} .0474834{col 41}{space 1}   -3.09{col 50}{space 3}0.002{col 58}{space 4}-.2399641{col 71}{space 3}-.0538325
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1286124{col 30}{space 2}  .032431{col 41}{space 1}    3.97{col 50}{space 3}0.000{col 58}{space 4} .0650488{col 71}{space 3}  .192176
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0756161{col 30}{space 2}  .067215{col 41}{space 1}    1.12{col 50}{space 3}0.261{col 58}{space 4}-.0561229{col 71}{space 3} .2073552
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .166081{col 30}{space 2} .3059406{col 41}{space 1}    0.54{col 50}{space 3}0.587{col 58}{space 4}-.4335516{col 71}{space 3} .7657135
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7087969{col 30}{space 2} .1118942{col 41}{space 1}    6.33{col 50}{space 3}0.000{col 58}{space 4} .4894883{col 71}{space 3} .9281054
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5544785{col 30}{space 2} .1542304{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .2521925{col 71}{space 3} .8567646
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .2243874{col 30}{space 2} .1110321{col 41}{space 1}    2.02{col 50}{space 3}0.043{col 58}{space 4} .0067684{col 71}{space 3} .4420064
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2271699{col 30}{space 2} .0982905{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4}  .034524{col 71}{space 3} .4198157
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0231532{col 30}{space 2} .0386089{col 41}{space 1}   -0.60{col 50}{space 3}0.549{col 58}{space 4}-.0988252{col 71}{space 3} .0525187
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .3641014{col 30}{space 2} .0618844{col 41}{space 1}    5.88{col 50}{space 3}0.000{col 58}{space 4} .2428103{col 71}{space 3} .4853926
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1234275{col 30}{space 2} .0509482{col 41}{space 1}    2.42{col 50}{space 3}0.015{col 58}{space 4} .0235709{col 71}{space 3} .2232841
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:  -13033.5}  
Iteration 1:{space 3}log pseudolikelihood = {res:  -13033.5}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   1474.27
{txt}Log pseudolikelihood = {res}  -13033.5{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0202267{col 30}{space 2} .0055105{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0094262{col 71}{space 3} .0310272
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0115391{col 30}{space 2} .0011279{col 41}{space 1}  -10.23{col 50}{space 3}0.000{col 58}{space 4}-.0137497{col 71}{space 3}-.0093285
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0036388{col 30}{space 2} .0010951{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0014925{col 71}{space 3} .0057851
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0182981{col 30}{space 2}  .017822{col 41}{space 1}   -1.03{col 50}{space 3}0.305{col 58}{space 4}-.0532287{col 71}{space 3} .0166324
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0002173{col 30}{space 2} .0002606{col 41}{space 1}    0.83{col 50}{space 3}0.404{col 58}{space 4}-.0002935{col 71}{space 3} .0007281
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0066107{col 30}{space 2} .0105647{col 41}{space 1}    0.63{col 50}{space 3}0.531{col 58}{space 4}-.0140956{col 71}{space 3} .0273171
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0588947{col 30}{space 2} .0078592{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .0434909{col 71}{space 3} .0742985
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0533494{col 30}{space 2} .0184167{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0172534{col 71}{space 3} .0894455
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0177013{col 30}{space 2}  .014578{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4} -.010871{col 71}{space 3} .0462736
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0381041{col 30}{space 2} .0204072{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4}-.0018933{col 71}{space 3} .0781015
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0369911{col 30}{space 2} .0156576{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0063028{col 71}{space 3} .0676794
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0283942{col 30}{space 2} .0127957{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-.0534732{col 71}{space 3}-.0033151
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0144764{col 30}{space 2} .0085679{col 41}{space 1}   -1.69{col 50}{space 3}0.091{col 58}{space 4}-.0312693{col 71}{space 3} .0023164
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0002292{col 30}{space 2} .0002839{col 41}{space 1}   -0.81{col 50}{space 3}0.419{col 58}{space 4}-.0007856{col 71}{space 3} .0003272
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0522494{col 30}{space 2}  .037677{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0215962{col 71}{space 3}  .126095
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0026669{col 30}{space 2} .0220034{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-.0457928{col 71}{space 3}  .040459
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .028885{col 30}{space 2} .0179166{col 41}{space 1}    1.61{col 50}{space 3}0.107{col 58}{space 4}-.0062309{col 71}{space 3}  .064001
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0272479{col 30}{space 2} .0235214{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.0188533{col 71}{space 3} .0733491
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0061922{col 30}{space 2} .0191326{col 41}{space 1}    0.32{col 50}{space 3}0.746{col 58}{space 4}-.0313069{col 71}{space 3} .0436913
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0665742{col 30}{space 2} .0155656{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0360662{col 71}{space 3} .0970823
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0064214{col 30}{space 2} .0063654{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.0188973{col 71}{space 3} .0060546
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0490383{col 30}{space 2}  .007041{col 41}{space 1}    6.96{col 50}{space 3}0.000{col 58}{space 4} .0352382{col 71}{space 3} .0628383
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  1.66127{col 30}{space 2} .0244391{col 41}{space 1}   67.98{col 50}{space 3}0.000{col 58}{space 4}  1.61337{col 71}{space 3}  1.70917
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .1137939{col 30}{space 2} .0309889{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0530568{col 71}{space 3}  .174531
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0649179{col 30}{space 2} .0063391{col 41}{space 1}  -10.24{col 50}{space 3}0.000{col 58}{space 4}-.0773422{col 71}{space 3}-.0524936
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0204717{col 30}{space 2} .0061574{col 41}{space 1}    3.32{col 50}{space 3}0.001{col 58}{space 4} .0084034{col 71}{space 3} .0325399
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1029438{col 30}{space 2} .1002755{col 41}{space 1}   -1.03{col 50}{space 3}0.305{col 58}{space 4}-.2994802{col 71}{space 3} .0935926
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0012226{col 30}{space 2}  .001466{col 41}{space 1}    0.83{col 50}{space 3}0.404{col 58}{space 4}-.0016508{col 71}{space 3} .0040959
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0371915{col 30}{space 2} .0594363{col 41}{space 1}    0.63{col 50}{space 3}0.531{col 58}{space 4}-.0793015{col 71}{space 3} .1536844
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3313369{col 30}{space 2} .0441749{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4} .2447556{col 71}{space 3} .4179181
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3001396{col 30}{space 2} .1035768{col 41}{space 1}    2.90{col 50}{space 3}0.004{col 58}{space 4} .0971328{col 71}{space 3} .5031464
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0995862{col 30}{space 2} .0820046{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0611398{col 71}{space 3} .2603122
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2143703{col 30}{space 2} .1147977{col 41}{space 1}    1.87{col 50}{space 3}0.062{col 58}{space 4} -.010629{col 71}{space 3} .4393696
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2081089{col 30}{space 2} .0880943{col 41}{space 1}    2.36{col 50}{space 3}0.018{col 58}{space 4} .0354473{col 71}{space 3} .3807705
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1597432{col 30}{space 2} .0719743{col 41}{space 1}   -2.22{col 50}{space 3}0.026{col 58}{space 4}-.3008103{col 71}{space 3}-.0186761
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0814433{col 30}{space 2} .0482057{col 41}{space 1}   -1.69{col 50}{space 3}0.091{col 58}{space 4}-.1759247{col 71}{space 3} .0130382
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0012895{col 30}{space 2} .0015971{col 41}{space 1}   -0.81{col 50}{space 3}0.419{col 58}{space 4}-.0044198{col 71}{space 3} .0018408
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2939507{col 30}{space 2} .2119694{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.1215017{col 71}{space 3}  .709403
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0150038{col 30}{space 2} .1237886{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4} -.257625{col 71}{space 3} .2276173
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1625048{col 30}{space 2} .1007985{col 41}{space 1}    1.61{col 50}{space 3}0.107{col 58}{space 4}-.0350566{col 71}{space 3} .3600663
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1532946{col 30}{space 2} .1323292{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-.1060658{col 71}{space 3} .4126549
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0348367{col 30}{space 2} .1076365{col 41}{space 1}    0.32{col 50}{space 3}0.746{col 58}{space 4} -.176127{col 71}{space 3} .2458005
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .3745411{col 30}{space 2} .0875028{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .2030388{col 71}{space 3} .5460434
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0361261{col 30}{space 2} .0358076{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.1063076{col 71}{space 3} .0340555
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2758853{col 30}{space 2}   .03949{col 41}{space 1}    6.99{col 50}{space 3}0.000{col 58}{space 4} .1984863{col 71}{space 3} .3532843
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-29946.379}  
Iteration 1:{space 3}log pseudolikelihood = {res:-29946.379}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   4174.15
{txt}Log pseudolikelihood = {res}-29946.379{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2}  .012146{col 30}{space 2} .0027018{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0068505{col 71}{space 3} .0174415
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0164059{col 30}{space 2} .0012356{col 41}{space 1}  -13.28{col 50}{space 3}0.000{col 58}{space 4}-.0188276{col 71}{space 3}-.0139841
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0028205{col 30}{space 2} .0008363{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.0044596{col 71}{space 3}-.0011815
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0246772{col 30}{space 2} .0094807{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0060953{col 71}{space 3} .0432591
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0006563{col 30}{space 2} .0001706{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4}  .000322{col 71}{space 3} .0009906
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0534884{col 30}{space 2} .0066597{col 41}{space 1}    8.03{col 50}{space 3}0.000{col 58}{space 4} .0404357{col 71}{space 3} .0665411
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0388431{col 30}{space 2} .0052759{col 41}{space 1}    7.36{col 50}{space 3}0.000{col 58}{space 4} .0285025{col 71}{space 3} .0491837
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0036672{col 30}{space 2} .0072961{col 41}{space 1}    0.50{col 50}{space 3}0.615{col 58}{space 4}-.0106329{col 71}{space 3} .0179674
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0322333{col 30}{space 2} .0075694{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .0173975{col 71}{space 3} .0470692
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0121989{col 30}{space 2}  .008422{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0043078{col 71}{space 3} .0287057
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0392884{col 30}{space 2}  .009305{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4}  .021051{col 71}{space 3} .0575259
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}    .0531{col 30}{space 2} .0076404{col 41}{space 1}    6.95{col 50}{space 3}0.000{col 58}{space 4}  .038125{col 71}{space 3} .0680749
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0116607{col 30}{space 2} .0085703{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.0051369{col 71}{space 3} .0284583
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0013918{col 30}{space 2} .0011697{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.0036844{col 71}{space 3} .0009009
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0636108{col 30}{space 2} .0099392{col 41}{space 1}    6.40{col 50}{space 3}0.000{col 58}{space 4} .0441304{col 71}{space 3} .0830913
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0184466{col 30}{space 2} .0096454{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4} -.000458{col 71}{space 3} .0373513
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1311413{col 30}{space 2} .0109871{col 41}{space 1}   11.94{col 50}{space 3}0.000{col 58}{space 4} .1096069{col 71}{space 3} .1526757
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1132832{col 30}{space 2} .0104169{col 41}{space 1}   10.87{col 50}{space 3}0.000{col 58}{space 4} .0928665{col 71}{space 3} .1336998
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0147581{col 30}{space 2} .0119891{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.0087401{col 71}{space 3} .0382563
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  -.01808{col 30}{space 2} .0096059{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.0369071{col 71}{space 3} .0007472
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0243157{col 30}{space 2} .0033481{col 41}{space 1}    7.26{col 50}{space 3}0.000{col 58}{space 4} .0177536{col 71}{space 3} .0308778
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0888286{col 30}{space 2} .0057082{col 41}{space 1}  -15.56{col 50}{space 3}0.000{col 58}{space 4}-.1000164{col 71}{space 3}-.0776408
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0848896{col 30}{space 2} .0057937{col 41}{space 1}  -14.65{col 50}{space 3}0.000{col 58}{space 4} -.096245{col 71}{space 3}-.0735342
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0627964{col 30}{space 2} .0057329{col 41}{space 1}  -10.95{col 50}{space 3}0.000{col 58}{space 4}-.0740326{col 71}{space 3}-.0515601
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.511269{col 30}{space 2}   .01802{col 41}{space 1}   83.87{col 50}{space 3}0.000{col 58}{space 4}  1.47595{col 71}{space 3} 1.546588
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0707095{col 30}{space 2} .0157263{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0398865{col 71}{space 3} .1015326
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0955086{col 30}{space 2}  .007187{col 41}{space 1}  -13.29{col 50}{space 3}0.000{col 58}{space 4}-.1095949{col 71}{space 3}-.0814223
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0164201{col 30}{space 2} .0048701{col 41}{space 1}   -3.37{col 50}{space 3}0.001{col 58}{space 4}-.0259652{col 71}{space 3}-.0068749
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1436612{col 30}{space 2} .0551876{col 41}{space 1}    2.60{col 50}{space 3}0.009{col 58}{space 4} .0354956{col 71}{space 3} .2518268
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0038206{col 30}{space 2} .0009929{col 41}{space 1}    3.85{col 50}{space 3}0.000{col 58}{space 4} .0018746{col 71}{space 3} .0057666
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .311389{col 30}{space 2} .0387331{col 41}{space 1}    8.04{col 50}{space 3}0.000{col 58}{space 4} .2354736{col 71}{space 3} .3873044
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2261295{col 30}{space 2} .0307127{col 41}{space 1}    7.36{col 50}{space 3}0.000{col 58}{space 4} .1659338{col 71}{space 3} .2863252
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0213493{col 30}{space 2} .0424751{col 41}{space 1}    0.50{col 50}{space 3}0.615{col 58}{space 4}-.0619005{col 71}{space 3}  .104599
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1876502{col 30}{space 2} .0440575{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .1012991{col 71}{space 3} .2740013
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0710174{col 30}{space 2} .0490282{col 41}{space 1}    1.45{col 50}{space 3}0.147{col 58}{space 4}-.0250761{col 71}{space 3} .1671109
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2287221{col 30}{space 2} .0541544{col 41}{space 1}    4.22{col 50}{space 3}0.000{col 58}{space 4} .1225815{col 71}{space 3} .3348627
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3091275{col 30}{space 2} .0444734{col 41}{space 1}    6.95{col 50}{space 3}0.000{col 58}{space 4} .2219613{col 71}{space 3} .3962938
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0678841{col 30}{space 2} .0498912{col 41}{space 1}    1.36{col 50}{space 3}0.174{col 58}{space 4}-.0299008{col 71}{space 3} .1656691
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0081022{col 30}{space 2} .0068096{col 41}{space 1}   -1.19{col 50}{space 3}0.234{col 58}{space 4}-.0214489{col 71}{space 3} .0052444
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3703178{col 30}{space 2} .0578621{col 41}{space 1}    6.40{col 50}{space 3}0.000{col 58}{space 4} .2569101{col 71}{space 3} .4837255
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1073893{col 30}{space 2}  .056154{col 41}{space 1}    1.91{col 50}{space 3}0.056{col 58}{space 4}-.0026705{col 71}{space 3} .2174491
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7634542{col 30}{space 2} .0639736{col 41}{space 1}   11.93{col 50}{space 3}0.000{col 58}{space 4} .6380682{col 71}{space 3} .8888403
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6594912{col 30}{space 2} .0606602{col 41}{space 1}   10.87{col 50}{space 3}0.000{col 58}{space 4} .5405994{col 71}{space 3}  .778383
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0859159{col 30}{space 2} .0697995{col 41}{space 1}    1.23{col 50}{space 3}0.218{col 58}{space 4}-.0508886{col 71}{space 3} .2227203
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1052547{col 30}{space 2} .0559237{col 41}{space 1}   -1.88{col 50}{space 3}0.060{col 58}{space 4}-.2148631{col 71}{space 3} .0043537
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1415567{col 30}{space 2} .0194822{col 41}{space 1}    7.27{col 50}{space 3}0.000{col 58}{space 4} .1033723{col 71}{space 3} .1797411
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5171259{col 30}{space 2} .0331246{col 41}{space 1}  -15.61{col 50}{space 3}0.000{col 58}{space 4} -.582049{col 71}{space 3}-.4522029
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4941946{col 30}{space 2}  .033571{col 41}{space 1}  -14.72{col 50}{space 3}0.000{col 58}{space 4}-.5599926{col 71}{space 3}-.4283967
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3655763{col 30}{space 2} .0332832{col 41}{space 1}  -10.98{col 50}{space 3}0.000{col 58}{space 4}-.4308102{col 71}{space 3}-.3003424
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23403.595}  
Iteration 1:{space 3}log pseudolikelihood = {res:-23403.595}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   1939.54
{txt}Log pseudolikelihood = {res}-23403.595{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0099118{col 30}{space 2} .0033516{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0033428{col 71}{space 3} .0164809
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0084846{col 30}{space 2} .0012866{col 41}{space 1}   -6.59{col 50}{space 3}0.000{col 58}{space 4}-.0110063{col 71}{space 3}-.0059629
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0007076{col 30}{space 2} .0010038{col 41}{space 1}   -0.70{col 50}{space 3}0.481{col 58}{space 4} -.002675{col 71}{space 3} .0012598
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0055339{col 30}{space 2} .0122133{col 41}{space 1}   -0.45{col 50}{space 3}0.650{col 58}{space 4}-.0294716{col 71}{space 3} .0184038
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0001097{col 30}{space 2} .0001908{col 41}{space 1}   -0.58{col 50}{space 3}0.565{col 58}{space 4}-.0004837{col 71}{space 3} .0002642
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0061757{col 30}{space 2}  .006726{col 41}{space 1}    0.92{col 50}{space 3}0.359{col 58}{space 4}-.0070069{col 71}{space 3} .0193584
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0557019{col 30}{space 2} .0067245{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4}  .042522{col 71}{space 3} .0688817
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0429493{col 30}{space 2} .0136115{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .0162712{col 71}{space 3} .0696274
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .051719{col 30}{space 2} .0089436{col 41}{space 1}    5.78{col 50}{space 3}0.000{col 58}{space 4} .0341899{col 71}{space 3} .0692481
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0041263{col 30}{space 2} .0095188{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0145303{col 71}{space 3} .0227829
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0240086{col 30}{space 2}  .006862{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .0105594{col 71}{space 3} .0374578
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0414814{col 30}{space 2} .0071363{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .0274946{col 71}{space 3} .0554683
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0318559{col 30}{space 2} .0062646{col 41}{space 1}   -5.09{col 50}{space 3}0.000{col 58}{space 4}-.0441342{col 71}{space 3}-.0195776
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0001547{col 30}{space 2} .0006036{col 41}{space 1}    0.26{col 50}{space 3}0.798{col 58}{space 4}-.0010283{col 71}{space 3} .0013378
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0274141{col 30}{space 2} .0058456{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4}  .015957{col 71}{space 3} .0388712
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}   .03964{col 30}{space 2} .0177352{col 41}{space 1}    2.24{col 50}{space 3}0.025{col 58}{space 4} .0048796{col 71}{space 3} .0744003
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0835514{col 30}{space 2} .0122203{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .0596002{col 71}{space 3} .1075027
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0953382{col 30}{space 2} .0124407{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .0709547{col 71}{space 3} .1197216
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0061028{col 30}{space 2} .0097802{col 41}{space 1}   -0.62{col 50}{space 3}0.533{col 58}{space 4}-.0252716{col 71}{space 3} .0130661
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0374037{col 30}{space 2} .0100207{col 41}{space 1}    3.73{col 50}{space 3}0.000{col 58}{space 4} .0177634{col 71}{space 3}  .057044
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0013368{col 30}{space 2} .0040342{col 41}{space 1}   -0.33{col 50}{space 3}0.740{col 58}{space 4}-.0092436{col 71}{space 3}   .00657
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0120202{col 30}{space 2} .0070622{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0018215{col 71}{space 3} .0258619
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0157723{col 30}{space 2} .0059022{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0042043{col 71}{space 3} .0273404
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0083639{col 30}{space 2} .0063491{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}  -.00408{col 71}{space 3} .0208079
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.534855{col 30}{space 2} .0195777{col 41}{space 1}   78.40{col 50}{space 3}0.000{col 58}{space 4} 1.496484{col 71}{space 3} 1.573227
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0567095{col 30}{space 2} .0191733{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0191305{col 71}{space 3} .0942885
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0485437{col 30}{space 2} .0073634{col 41}{space 1}   -6.59{col 50}{space 3}0.000{col 58}{space 4}-.0629756{col 71}{space 3}-.0341117
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0040485{col 30}{space 2} .0057435{col 41}{space 1}   -0.70{col 50}{space 3}0.481{col 58}{space 4}-.0153055{col 71}{space 3} .0072084
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0316618{col 30}{space 2} .0698802{col 41}{space 1}   -0.45{col 50}{space 3}0.650{col 58}{space 4}-.1686244{col 71}{space 3} .1053008
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0006279{col 30}{space 2} .0010915{col 41}{space 1}   -0.58{col 50}{space 3}0.565{col 58}{space 4}-.0027673{col 71}{space 3} .0015114
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0353337{col 30}{space 2} .0384841{col 41}{space 1}    0.92{col 50}{space 3}0.359{col 58}{space 4}-.0400937{col 71}{space 3} .1107611
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3186918{col 30}{space 2} .0384884{col 41}{space 1}    8.28{col 50}{space 3}0.000{col 58}{space 4}  .243256{col 71}{space 3} .3941276
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2457294{col 30}{space 2}  .077871{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4}  .093105{col 71}{space 3} .3983538
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2959044{col 30}{space 2} .0511649{col 41}{space 1}    5.78{col 50}{space 3}0.000{col 58}{space 4} .1956231{col 71}{space 3} .3961857
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .023608{col 30}{space 2}   .05446{col 41}{space 1}    0.43{col 50}{space 3}0.665{col 58}{space 4}-.0831316{col 71}{space 3} .1303476
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1373627{col 30}{space 2} .0392519{col 41}{space 1}    3.50{col 50}{space 3}0.000{col 58}{space 4} .0604304{col 71}{space 3}  .214295
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2373314{col 30}{space 2} .0408315{col 41}{space 1}    5.81{col 50}{space 3}0.000{col 58}{space 4} .1573031{col 71}{space 3} .3173596
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1822599{col 30}{space 2} .0358435{col 41}{space 1}   -5.08{col 50}{space 3}0.000{col 58}{space 4}-.2525118{col 71}{space 3}-.1120079
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0008853{col 30}{space 2} .0034535{col 41}{space 1}    0.26{col 50}{space 3}0.798{col 58}{space 4}-.0058834{col 71}{space 3} .0076539
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1568465{col 30}{space 2} .0334452{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0912951{col 71}{space 3} .2223979
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2267955{col 30}{space 2} .1014778{col 41}{space 1}    2.23{col 50}{space 3}0.025{col 58}{space 4} .0279027{col 71}{space 3} .4256884
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}   .47803{col 30}{space 2} .0699199{col 41}{space 1}    6.84{col 50}{space 3}0.000{col 58}{space 4} .3409894{col 71}{space 3} .6150705
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5454664{col 30}{space 2} .0711467{col 41}{space 1}    7.67{col 50}{space 3}0.000{col 58}{space 4} .4060214{col 71}{space 3} .6849115
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0349163{col 30}{space 2} .0559546{col 41}{space 1}   -0.62{col 50}{space 3}0.533{col 58}{space 4}-.1445854{col 71}{space 3} .0747528
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .214001{col 30}{space 2} .0573132{col 41}{space 1}    3.73{col 50}{space 3}0.000{col 58}{space 4} .1016692{col 71}{space 3} .3263328
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2}-.0076483{col 30}{space 2} .0230799{col 41}{space 1}   -0.33{col 50}{space 3}0.740{col 58}{space 4}-.0528841{col 71}{space 3} .0375876
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0687723{col 30}{space 2} .0404174{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0104443{col 71}{space 3} .1479888
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0902395{col 30}{space 2} .0337697{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0240521{col 71}{space 3} .1564269
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0478532{col 30}{space 2} .0363173{col 41}{space 1}    1.32{col 50}{space 3}0.188{col 58}{space 4}-.0233275{col 71}{space 3} .1190338
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9  pdd9_vill sum_vill  $xlist  pdd9_mean_vill $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-31890.497}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31890.497}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 49}Wald chi2({res}26{txt}){col 67}= {res}   2374.07
{txt}Log pseudolikelihood = {res}-31890.497{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0046435{col 30}{space 2} .0023962{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4} -.000053{col 71}{space 3} .0093399
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0066388{col 30}{space 2} .0008635{col 41}{space 1}   -7.69{col 50}{space 3}0.000{col 58}{space 4}-.0083313{col 71}{space 3}-.0049464
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0044727{col 30}{space 2} .0009871{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4}  .002538{col 71}{space 3} .0064073
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0031864{col 30}{space 2} .0117835{col 41}{space 1}    0.27{col 50}{space 3}0.787{col 58}{space 4}-.0199089{col 71}{space 3} .0262817
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003161{col 30}{space 2} .0001906{col 41}{space 1}   -1.66{col 50}{space 3}0.097{col 58}{space 4}-.0006897{col 71}{space 3} .0000576
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}   .00703{col 30}{space 2} .0064536{col 41}{space 1}    1.09{col 50}{space 3}0.276{col 58}{space 4}-.0056189{col 71}{space 3} .0196789
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0706082{col 30}{space 2} .0065832{col 41}{space 1}   10.73{col 50}{space 3}0.000{col 58}{space 4} .0577053{col 71}{space 3} .0835111
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0351091{col 30}{space 2} .0091647{col 41}{space 1}    3.83{col 50}{space 3}0.000{col 58}{space 4} .0171466{col 71}{space 3} .0530716
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0465374{col 30}{space 2} .0070294{col 41}{space 1}    6.62{col 50}{space 3}0.000{col 58}{space 4}   .03276{col 71}{space 3} .0603148
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0548092{col 30}{space 2} .0064764{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .0421157{col 71}{space 3} .0675027
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0064076{col 30}{space 2} .0054753{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0043238{col 71}{space 3} .0171391
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0365787{col 30}{space 2}   .00572{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .0253676{col 71}{space 3} .0477897
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0057396{col 30}{space 2} .0049455{col 41}{space 1}   -1.16{col 50}{space 3}0.246{col 58}{space 4}-.0154326{col 71}{space 3} .0039534
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005875{col 30}{space 2} .0003711{col 41}{space 1}    1.58{col 50}{space 3}0.113{col 58}{space 4}-.0001399{col 71}{space 3} .0013148
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0065984{col 30}{space 2} .0054357{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4}-.0040554{col 71}{space 3} .0172523
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0153311{col 30}{space 2} .0140462{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4} -.012199{col 71}{space 3} .0428612
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0621844{col 30}{space 2} .0116512{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .0393485{col 71}{space 3} .0850204
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0579645{col 30}{space 2} .0116002{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .0352286{col 71}{space 3} .0807005
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0141287{col 30}{space 2} .0099036{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4} -.005282{col 71}{space 3} .0335395
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0513914{col 30}{space 2} .0095941{col 41}{space 1}    5.36{col 50}{space 3}0.000{col 58}{space 4} .0325874{col 71}{space 3} .0701955
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .0343511{col 30}{space 2} .0039475{col 41}{space 1}    8.70{col 50}{space 3}0.000{col 58}{space 4} .0266141{col 71}{space 3} .0420881
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0275029{col 30}{space 2} .0074949{col 41}{space 1}   -3.67{col 50}{space 3}0.000{col 58}{space 4}-.0421926{col 71}{space 3}-.0128131
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0156188{col 30}{space 2} .0064081{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4}-.0281785{col 71}{space 3}-.0030591
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .061991{col 30}{space 2} .0061824{col 41}{space 1}   10.03{col 50}{space 3}0.000{col 58}{space 4} .0498737{col 71}{space 3} .0741083
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}  .020477{col 30}{space 2} .0062619{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0082039{col 71}{space 3} .0327502
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0545188{col 30}{space 2} .0057141{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .0433193{col 71}{space 3} .0657184
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.308611{col 30}{space 2} .0236997{col 41}{space 1}   55.22{col 50}{space 3}0.000{col 58}{space 4}  1.26216{col 71}{space 3} 1.355061
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_vill sum_vill hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_vill year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_vill {c |}{col 18}{res}{space 2} .0259539{col 30}{space 2} .0133928{col 41}{space 1}    1.94{col 50}{space 3}0.053{col 58}{space 4}-.0002955{col 71}{space 3} .0522032
{txt}{space 8}sum_vill {c |}{col 18}{res}{space 2}-.0371065{col 30}{space 2} .0048227{col 41}{space 1}   -7.69{col 50}{space 3}0.000{col 58}{space 4}-.0465589{col 71}{space 3}-.0276541
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .024999{col 30}{space 2} .0055156{col 41}{space 1}    4.53{col 50}{space 3}0.000{col 58}{space 4} .0141887{col 71}{space 3} .0358094
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0178097{col 30}{space 2} .0658607{col 41}{space 1}    0.27{col 50}{space 3}0.787{col 58}{space 4} -.111275{col 71}{space 3} .1468943
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0017665{col 30}{space 2} .0010654{col 41}{space 1}   -1.66{col 50}{space 3}0.097{col 58}{space 4}-.0038548{col 71}{space 3} .0003217
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0392928{col 30}{space 2} .0360705{col 41}{space 1}    1.09{col 50}{space 3}0.276{col 58}{space 4}-.0314041{col 71}{space 3} .1099897
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3946505{col 30}{space 2} .0367726{col 41}{space 1}   10.73{col 50}{space 3}0.000{col 58}{space 4} .3225775{col 71}{space 3} .4667235
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1962353{col 30}{space 2}  .051216{col 41}{space 1}    3.83{col 50}{space 3}0.000{col 58}{space 4} .0958539{col 71}{space 3} .2966168
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2601115{col 30}{space 2} .0392638{col 41}{space 1}    6.62{col 50}{space 3}0.000{col 58}{space 4} .1831559{col 71}{space 3}  .337067
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3063449{col 30}{space 2} .0361945{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .2354051{col 71}{space 3} .3772848
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0358142{col 30}{space 2}  .030607{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0241744{col 71}{space 3} .0958028
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2044492{col 30}{space 2} .0319811{col 41}{space 1}    6.39{col 50}{space 3}0.000{col 58}{space 4} .1417673{col 71}{space 3}  .267131
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0320805{col 30}{space 2} .0276426{col 41}{space 1}   -1.16{col 50}{space 3}0.246{col 58}{space 4}-.0862589{col 71}{space 3}  .022098
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0032835{col 30}{space 2} .0020744{col 41}{space 1}    1.58{col 50}{space 3}0.113{col 58}{space 4}-.0007823{col 71}{space 3} .0073494
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0368807{col 30}{space 2}  .030383{col 41}{space 1}    1.21{col 50}{space 3}0.225{col 58}{space 4} -.022669{col 71}{space 3} .0964304
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0856901{col 30}{space 2} .0785113{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4}-.0681893{col 71}{space 3} .2395695
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3475676{col 30}{space 2} .0650841{col 41}{space 1}    5.34{col 50}{space 3}0.000{col 58}{space 4} .2200051{col 71}{space 3} .4751301
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3239813{col 30}{space 2} .0647793{col 41}{space 1}    5.00{col 50}{space 3}0.000{col 58}{space 4} .1970163{col 71}{space 3} .4509463
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0789698{col 30}{space 2} .0553594{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-.0295327{col 71}{space 3} .1874723
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2872421{col 30}{space 2} .0536308{col 41}{space 1}    5.36{col 50}{space 3}0.000{col 58}{space 4} .1821276{col 71}{space 3} .3923565
{txt}{space 2}pdd9_mean_vill {c |}{col 18}{res}{space 2} .1919985{col 30}{space 2} .0220228{col 41}{space 1}    8.72{col 50}{space 3}0.000{col 58}{space 4} .1488347{col 71}{space 3} .2351623
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1537217{col 30}{space 2} .0418659{col 41}{space 1}   -3.67{col 50}{space 3}0.000{col 58}{space 4}-.2357773{col 71}{space 3}-.0716661
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0872983{col 30}{space 2} .0358243{col 41}{space 1}   -2.44{col 50}{space 3}0.015{col 58}{space 4}-.1575126{col 71}{space 3} -.017084
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3464863{col 30}{space 2} .0345342{col 41}{space 1}   10.03{col 50}{space 3}0.000{col 58}{space 4} .2788006{col 71}{space 3} .4141721
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1144524{col 30}{space 2} .0349956{col 41}{space 1}    3.27{col 50}{space 3}0.001{col 58}{space 4} .0458622{col 71}{space 3} .1830426
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .3047223{col 30}{space 2} .0319543{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4}  .242093{col 71}{space 3} .3673515
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S25_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_vill    $xlist  pdd9_mean_vill sum_vill  )
{res}{txt}(note: file S25_poisson.rtf not found)
(output written to {browse  `"S25_poisson.rtf"'})

{com}. 
. 
. 
. 
. 
. ********************************************************************************
. *                                   S26                                        *
. ********************************************************************************
. *                          town_village_level                                  *
. eststo clear
{txt}
{com}. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-128807.41}  
Iteration 1:{space 3}log pseudolikelihood = {res: -128807.4}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 49}Wald chi2({res}36{txt}){col 67}= {res}  18216.38
{txt}Log pseudolikelihood = {res} -128807.4{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0049252{col 30}{space 2} .0013435{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4}  .002292{col 71}{space 3} .0075583
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0003538{col 30}{space 2} .0000434{col 41}{space 1}   -8.15{col 50}{space 3}0.000{col 58}{space 4}-.0004388{col 71}{space 3}-.0002687
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0001065{col 30}{space 2} .0004542{col 41}{space 1}   -0.23{col 50}{space 3}0.815{col 58}{space 4}-.0009967{col 71}{space 3} .0007837
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0016894{col 30}{space 2} .0054237{col 41}{space 1}    0.31{col 50}{space 3}0.755{col 58}{space 4}-.0089408{col 71}{space 3} .0123195
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0000948{col 30}{space 2} .0000885{col 41}{space 1}    1.07{col 50}{space 3}0.284{col 58}{space 4}-.0000787{col 71}{space 3} .0002683
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0111351{col 30}{space 2} .0032538{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0047577{col 71}{space 3} .0175125
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .065849{col 30}{space 2} .0029216{col 41}{space 1}   22.54{col 50}{space 3}0.000{col 58}{space 4} .0601228{col 71}{space 3} .0715753
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0206869{col 30}{space 2} .0049759{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0109344{col 71}{space 3} .0304395
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0352315{col 30}{space 2} .0037048{col 41}{space 1}    9.51{col 50}{space 3}0.000{col 58}{space 4} .0279702{col 71}{space 3} .0424927
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0269612{col 30}{space 2} .0040466{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4}   .01903{col 71}{space 3} .0348923
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0230751{col 30}{space 2} .0035295{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} .0161574{col 71}{space 3} .0299928
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0394419{col 30}{space 2} .0033149{col 41}{space 1}   11.90{col 50}{space 3}0.000{col 58}{space 4} .0329449{col 71}{space 3}  .045939
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0212832{col 30}{space 2} .0028546{col 41}{space 1}   -7.46{col 50}{space 3}0.000{col 58}{space 4} -.026878{col 71}{space 3}-.0156883
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0000894{col 30}{space 2} .0002121{col 41}{space 1}   -0.42{col 50}{space 3}0.673{col 58}{space 4}-.0005051{col 71}{space 3} .0003263
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0341517{col 30}{space 2} .0031599{col 41}{space 1}   10.81{col 50}{space 3}0.000{col 58}{space 4} .0279584{col 71}{space 3} .0403451
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0000202{col 30}{space 2} .0066385{col 41}{space 1}   -0.00{col 50}{space 3}0.998{col 58}{space 4}-.0130314{col 71}{space 3}  .012991
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1090118{col 30}{space 2} .0054044{col 41}{space 1}   20.17{col 50}{space 3}0.000{col 58}{space 4} .0984193{col 71}{space 3} .1196042
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1143868{col 30}{space 2} .0054281{col 41}{space 1}   21.07{col 50}{space 3}0.000{col 58}{space 4} .1037479{col 71}{space 3} .1250256
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0235556{col 30}{space 2} .0051682{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4} .0134261{col 71}{space 3} .0336852
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0286145{col 30}{space 2} .0046631{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4}  .019475{col 71}{space 3}  .037754
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0161045{col 30}{space 2} .0017472{col 41}{space 1}    9.22{col 50}{space 3}0.000{col 58}{space 4}   .01268{col 71}{space 3}  .019529
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.0829436{col 30}{space 2} .0063598{col 41}{space 1}  -13.04{col 50}{space 3}0.000{col 58}{space 4}-.0954085{col 71}{space 3}-.0704787
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.3293965{col 30}{space 2} .0066418{col 41}{space 1}  -49.59{col 50}{space 3}0.000{col 58}{space 4}-.3424141{col 71}{space 3}-.3163789
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.1084037{col 30}{space 2} .0062881{col 41}{space 1}  -17.24{col 50}{space 3}0.000{col 58}{space 4}-.1207282{col 71}{space 3}-.0960792
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.0727192{col 30}{space 2} .0062113{col 41}{space 1}  -11.71{col 50}{space 3}0.000{col 58}{space 4}-.0848931{col 71}{space 3}-.0605453
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .0418701{col 30}{space 2} .0075864{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4}  .027001{col 71}{space 3} .0567391
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0540089{col 30}{space 2} .0089575{col 41}{space 1}   -6.03{col 50}{space 3}0.000{col 58}{space 4}-.0715653{col 71}{space 3}-.0364524
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0059824{col 30}{space 2} .0065656{col 41}{space 1}   -0.91{col 50}{space 3}0.362{col 58}{space 4}-.0188507{col 71}{space 3}  .006886
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0168004{col 30}{space 2} .0074026{col 41}{space 1}   -2.27{col 50}{space 3}0.023{col 58}{space 4}-.0313092{col 71}{space 3}-.0022915
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}  -.00485{col 30}{space 2} .0066302{col 41}{space 1}   -0.73{col 50}{space 3}0.464{col 58}{space 4} -.017845{col 71}{space 3} .0081449
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0090346{col 30}{space 2}  .007407{col 41}{space 1}    1.22{col 50}{space 3}0.223{col 58}{space 4}-.0054829{col 71}{space 3} .0235521
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0379541{col 30}{space 2} .0073964{col 41}{space 1}   -5.13{col 50}{space 3}0.000{col 58}{space 4}-.0524507{col 71}{space 3}-.0234575
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0205907{col 30}{space 2} .0071238{col 41}{space 1}    2.89{col 50}{space 3}0.004{col 58}{space 4} .0066282{col 71}{space 3} .0345531
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0489865{col 30}{space 2} .0105254{col 41}{space 1}   -4.65{col 50}{space 3}0.000{col 58}{space 4}-.0696159{col 71}{space 3}-.0283572
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0617047{col 30}{space 2} .0073461{col 41}{space 1}    8.40{col 50}{space 3}0.000{col 58}{space 4} .0473066{col 71}{space 3} .0761028
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0241151{col 30}{space 2} .0072688{col 41}{space 1}   -3.32{col 50}{space 3}0.001{col 58}{space 4}-.0383618{col 71}{space 3}-.0098685
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  1.46068{col 30}{space 2} .0119091{col 41}{space 1}  122.65{col 50}{space 3}0.000{col 58}{space 4} 1.437339{col 71}{space 3} 1.484021
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0268913{col 30}{space 2} .0073349{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0125151{col 71}{space 3} .0412675
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0019315{col 30}{space 2}  .000237{col 41}{space 1}   -8.15{col 50}{space 3}0.000{col 58}{space 4}-.0023959{col 71}{space 3}-.0014671
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0005816{col 30}{space 2} .0024799{col 41}{space 1}   -0.23{col 50}{space 3}0.815{col 58}{space 4} -.005442{col 71}{space 3} .0042789
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0092239{col 30}{space 2}  .029613{col 41}{space 1}    0.31{col 50}{space 3}0.755{col 58}{space 4}-.0488166{col 71}{space 3} .0672643
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005177{col 30}{space 2} .0004833{col 41}{space 1}    1.07{col 50}{space 3}0.284{col 58}{space 4}-.0004295{col 71}{space 3} .0014649
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0607978{col 30}{space 2} .0177667{col 41}{space 1}    3.42{col 50}{space 3}0.001{col 58}{space 4} .0259758{col 71}{space 3} .0956198
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3595354{col 30}{space 2} .0159502{col 41}{space 1}   22.54{col 50}{space 3}0.000{col 58}{space 4} .3282737{col 71}{space 3} .3907972
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1129506{col 30}{space 2} .0271678{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0597027{col 71}{space 3} .1661985
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1923636{col 30}{space 2} .0202253{col 41}{space 1}    9.51{col 50}{space 3}0.000{col 58}{space 4} .1527227{col 71}{space 3} .2320044
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1472077{col 30}{space 2} .0220929{col 41}{space 1}    6.66{col 50}{space 3}0.000{col 58}{space 4} .1039065{col 71}{space 3}  .190509
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}   .12599{col 30}{space 2} .0192714{col 41}{space 1}    6.54{col 50}{space 3}0.000{col 58}{space 4} .0882187{col 71}{space 3} .1637613
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2153528{col 30}{space 2} .0180999{col 41}{space 1}   11.90{col 50}{space 3}0.000{col 58}{space 4} .1798776{col 71}{space 3} .2508279
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.116206{col 30}{space 2} .0155867{col 41}{space 1}   -7.46{col 50}{space 3}0.000{col 58}{space 4}-.1467553{col 71}{space 3}-.0856567
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004882{col 30}{space 2} .0011579{col 41}{space 1}   -0.42{col 50}{space 3}0.673{col 58}{space 4}-.0027577{col 71}{space 3} .0017813
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1864682{col 30}{space 2} .0172547{col 41}{space 1}   10.81{col 50}{space 3}0.000{col 58}{space 4} .1526495{col 71}{space 3} .2202869
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0001102{col 30}{space 2} .0362461{col 41}{space 1}   -0.00{col 50}{space 3}0.998{col 58}{space 4}-.0711513{col 71}{space 3} .0709309
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .5952036{col 30}{space 2} .0294909{col 41}{space 1}   20.18{col 50}{space 3}0.000{col 58}{space 4} .5374026{col 71}{space 3} .6530046
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6245511{col 30}{space 2} .0296158{col 41}{space 1}   21.09{col 50}{space 3}0.000{col 58}{space 4} .5665052{col 71}{space 3}  .682597
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1286136{col 30}{space 2} .0282197{col 41}{space 1}    4.56{col 50}{space 3}0.000{col 58}{space 4}  .073304{col 71}{space 3} .1839233
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .156235{col 30}{space 2} .0254585{col 41}{space 1}    6.14{col 50}{space 3}0.000{col 58}{space 4} .1063373{col 71}{space 3} .2061327
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0879304{col 30}{space 2} .0095384{col 41}{space 1}    9.22{col 50}{space 3}0.000{col 58}{space 4} .0692354{col 71}{space 3} .1066254
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.4839988{col 30}{space 2} .0377068{col 41}{space 1}  -12.84{col 50}{space 3}0.000{col 58}{space 4}-.5579029{col 71}{space 3}-.4100947
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.706479{col 30}{space 2} .0362371{col 41}{space 1}  -47.09{col 50}{space 3}0.000{col 58}{space 4}-1.777503{col 71}{space 3}-1.635456
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.6246908{col 30}{space 2} .0371173{col 41}{space 1}  -16.83{col 50}{space 3}0.000{col 58}{space 4}-.6974394{col 71}{space 3}-.5519423
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.4264833{col 30}{space 2} .0369682{col 41}{space 1}  -11.54{col 50}{space 3}0.000{col 58}{space 4}-.4989397{col 71}{space 3} -.354027
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2600013{col 30}{space 2} .0471317{col 41}{space 1}    5.52{col 50}{space 3}0.000{col 58}{space 4} .1676249{col 71}{space 3} .3523776
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2874646{col 30}{space 2}  .047768{col 41}{space 1}   -6.02{col 50}{space 3}0.000{col 58}{space 4}-.3810881{col 71}{space 3} -.193841
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0326113{col 30}{space 2} .0358738{col 41}{space 1}   -0.91{col 50}{space 3}0.363{col 58}{space 4}-.1029227{col 71}{space 3} .0377001
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0910898{col 30}{space 2} .0403255{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-.1701264{col 71}{space 3}-.0120532
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0264538{col 30}{space 2} .0362226{col 41}{space 1}   -0.73{col 50}{space 3}0.465{col 58}{space 4}-.0974487{col 71}{space 3} .0445411
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0496211{col 30}{space 2} .0405806{col 41}{space 1}    1.22{col 50}{space 3}0.221{col 58}{space 4}-.0299155{col 71}{space 3} .1291577
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2036279{col 30}{space 2} .0400284{col 41}{space 1}   -5.09{col 50}{space 3}0.000{col 58}{space 4}-.2820821{col 71}{space 3}-.1251737
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1137479{col 30}{space 2} .0390876{col 41}{space 1}    2.91{col 50}{space 3}0.004{col 58}{space 4} .0371377{col 71}{space 3} .1903581
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2613829{col 30}{space 2} .0558461{col 41}{space 1}   -4.68{col 50}{space 3}0.000{col 58}{space 4}-.3708393{col 71}{space 3}-.1519264
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3480007{col 30}{space 2} .0407464{col 41}{space 1}    8.54{col 50}{space 3}0.000{col 58}{space 4} .2681393{col 71}{space 3} .4278622
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1302741{col 30}{space 2} .0395216{col 41}{space 1}   -3.30{col 50}{space 3}0.001{col 58}{space 4} -.207735{col 71}{space 3}-.0528132
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-20901.245}  
Iteration 1:{space 3}log pseudolikelihood = {res:-20901.245}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   2537.06
{txt}Log pseudolikelihood = {res}-20901.245{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0120126{col 30}{space 2} .0037958{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4}  .004573{col 71}{space 3} .0194523
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0012815{col 30}{space 2} .0001464{col 41}{space 1}   -8.75{col 50}{space 3}0.000{col 58}{space 4}-.0015685{col 71}{space 3}-.0009945
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0114947{col 30}{space 2} .0017129{col 41}{space 1}    6.71{col 50}{space 3}0.000{col 58}{space 4} .0081374{col 71}{space 3}  .014852
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0146561{col 30}{space 2} .0148729{col 41}{space 1}   -0.99{col 50}{space 3}0.324{col 58}{space 4}-.0438065{col 71}{space 3} .0144943
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011455{col 30}{space 2} .0002468{col 41}{space 1}   -4.64{col 50}{space 3}0.000{col 58}{space 4}-.0016293{col 71}{space 3}-.0006617
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0081811{col 30}{space 2} .0089377{col 41}{space 1}   -0.92{col 50}{space 3}0.360{col 58}{space 4}-.0256987{col 71}{space 3} .0093365
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0902113{col 30}{space 2} .0076517{col 41}{space 1}   11.79{col 50}{space 3}0.000{col 58}{space 4} .0752142{col 71}{space 3} .1052085
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0466461{col 30}{space 2} .0321698{col 41}{space 1}   -1.45{col 50}{space 3}0.147{col 58}{space 4}-.1096979{col 71}{space 3} .0164056
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0422121{col 30}{space 2} .0089471{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .0246761{col 71}{space 3} .0597482
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0412721{col 30}{space 2} .0106416{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0204149{col 71}{space 3} .0621293
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0151894{col 30}{space 2} .0132995{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0108772{col 71}{space 3} .0412559
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0504821{col 30}{space 2} .0114817{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .0279784{col 71}{space 3} .0729859
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0479496{col 30}{space 2} .0078896{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4}-.0634129{col 71}{space 3}-.0324863
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0030103{col 30}{space 2} .0008177{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0014077{col 71}{space 3} .0046128
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0803811{col 30}{space 2} .0076637{col 41}{space 1}   10.49{col 50}{space 3}0.000{col 58}{space 4} .0653604{col 71}{space 3} .0954018
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1679209{col 30}{space 2} .0496735{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0705626{col 71}{space 3} .2652792
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1035267{col 30}{space 2} .0133605{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .0773406{col 71}{space 3} .1297128
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1059638{col 30}{space 2} .0152794{col 41}{space 1}    6.94{col 50}{space 3}0.000{col 58}{space 4} .0760168{col 71}{space 3} .1359108
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1000611{col 30}{space 2} .0202251{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .0604206{col 71}{space 3} .1397015
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0231206{col 30}{space 2} .0145011{col 41}{space 1}    1.59{col 50}{space 3}0.111{col 58}{space 4} -.005301{col 71}{space 3} .0515422
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0123741{col 30}{space 2} .0045919{col 41}{space 1}    2.69{col 50}{space 3}0.007{col 58}{space 4} .0033742{col 71}{space 3} .0213741
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0290488{col 30}{space 2} .0053374{col 41}{space 1}   -5.44{col 50}{space 3}0.000{col 58}{space 4}-.0395098{col 71}{space 3}-.0185877
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.110148{col 30}{space 2} .0228513{col 41}{space 1}   48.58{col 50}{space 3}0.000{col 58}{space 4}  1.06536{col 71}{space 3} 1.154936
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0508153{col 30}{space 2} .0160579{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} .0193424{col 71}{space 3} .0822882
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0054209{col 30}{space 2} .0006202{col 41}{space 1}   -8.74{col 50}{space 3}0.000{col 58}{space 4}-.0066365{col 71}{space 3}-.0042054
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0486244{col 30}{space 2} .0072432{col 41}{space 1}    6.71{col 50}{space 3}0.000{col 58}{space 4} .0344279{col 71}{space 3} .0628209
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0619976{col 30}{space 2} .0629113{col 41}{space 1}   -0.99{col 50}{space 3}0.324{col 58}{space 4}-.1853014{col 71}{space 3} .0613062
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0048457{col 30}{space 2} .0010445{col 41}{space 1}   -4.64{col 50}{space 3}0.000{col 58}{space 4} -.006893{col 71}{space 3}-.0027985
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0346072{col 30}{space 2} .0378062{col 41}{space 1}   -0.92{col 50}{space 3}0.360{col 58}{space 4} -.108706{col 71}{space 3} .0394915
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3816074{col 30}{space 2} .0323998{col 41}{space 1}   11.78{col 50}{space 3}0.000{col 58}{space 4} .3181049{col 71}{space 3} .4451099
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.1973201{col 30}{space 2} .1360871{col 41}{space 1}   -1.45{col 50}{space 3}0.147{col 58}{space 4}-.4640459{col 71}{space 3} .0694057
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1785636{col 30}{space 2} .0378537{col 41}{space 1}    4.72{col 50}{space 3}0.000{col 58}{space 4} .1043717{col 71}{space 3} .2527555
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1745872{col 30}{space 2}  .045007{col 41}{space 1}    3.88{col 50}{space 3}0.000{col 58}{space 4} .0863752{col 71}{space 3} .2627993
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0642533{col 30}{space 2} .0562575{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0460094{col 71}{space 3} .1745159
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2135469{col 30}{space 2} .0485719{col 41}{space 1}    4.40{col 50}{space 3}0.000{col 58}{space 4} .1183477{col 71}{space 3} .3087461
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.202834{col 30}{space 2} .0333833{col 41}{space 1}   -6.08{col 50}{space 3}0.000{col 58}{space 4} -.268264{col 71}{space 3}-.1374039
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0127339{col 30}{space 2} .0034584{col 41}{space 1}    3.68{col 50}{space 3}0.000{col 58}{space 4} .0059555{col 71}{space 3} .0195123
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3400241{col 30}{space 2}  .032465{col 41}{space 1}   10.47{col 50}{space 3}0.000{col 58}{space 4} .2763938{col 71}{space 3} .4036543
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7103304{col 30}{space 2}  .210129{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .2984851{col 71}{space 3} 1.122176
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4379335{col 30}{space 2} .0565383{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .3271203{col 71}{space 3} .5487466
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4482427{col 30}{space 2} .0646704{col 41}{space 1}    6.93{col 50}{space 3}0.000{col 58}{space 4}  .321491{col 71}{space 3} .5749944
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4232732{col 30}{space 2} .0855045{col 41}{space 1}    4.95{col 50}{space 3}0.000{col 58}{space 4} .2556874{col 71}{space 3}  .590859
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0978034{col 30}{space 2} .0613327{col 41}{space 1}    1.59{col 50}{space 3}0.111{col 58}{space 4}-.0224065{col 71}{space 3} .2180134
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0523445{col 30}{space 2} .0194202{col 41}{space 1}    2.70{col 50}{space 3}0.007{col 58}{space 4} .0142816{col 71}{space 3} .0904073
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1228805{col 30}{space 2} .0225676{col 41}{space 1}   -5.45{col 50}{space 3}0.000{col 58}{space 4}-.1671122{col 71}{space 3}-.0786489
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-9229.0429}  
Iteration 1:{space 3}log pseudolikelihood = {res:-9229.0425}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   1570.64
{txt}Log pseudolikelihood = {res}-9229.0425{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0061331{col 30}{space 2} .0043691{col 41}{space 1}    1.40{col 50}{space 3}0.160{col 58}{space 4}-.0024301{col 71}{space 3} .0146963
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0025884{col 30}{space 2} .0006129{col 41}{space 1}   -4.22{col 50}{space 3}0.000{col 58}{space 4}-.0037897{col 71}{space 3}-.0013871
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0015531{col 30}{space 2} .0020069{col 41}{space 1}   -0.77{col 50}{space 3}0.439{col 58}{space 4}-.0054866{col 71}{space 3} .0023803
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0426193{col 30}{space 2} .0183683{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4}-.0786205{col 71}{space 3}-.0066181
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0002254{col 30}{space 2}    .0003{col 41}{space 1}   -0.75{col 50}{space 3}0.452{col 58}{space 4}-.0008134{col 71}{space 3} .0003626
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0120846{col 30}{space 2} .0109668{col 41}{space 1}   -1.10{col 50}{space 3}0.270{col 58}{space 4} -.033579{col 71}{space 3} .0094099
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0645261{col 30}{space 2} .0109876{col 41}{space 1}    5.87{col 50}{space 3}0.000{col 58}{space 4} .0429909{col 71}{space 3} .0860613
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0382916{col 30}{space 2} .0278704{col 41}{space 1}    1.37{col 50}{space 3}0.169{col 58}{space 4}-.0163334{col 71}{space 3} .0929166
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0184853{col 30}{space 2} .0119888{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0050122{col 71}{space 3} .0419829
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}  .030225{col 30}{space 2} .0201986{col 41}{space 1}    1.50{col 50}{space 3}0.135{col 58}{space 4}-.0093634{col 71}{space 3} .0698135
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0229654{col 30}{space 2} .0132635{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0030305{col 71}{space 3} .0489614
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0420741{col 30}{space 2} .0093421{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0237639{col 71}{space 3} .0603842
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0283107{col 30}{space 2} .0078678{col 41}{space 1}   -3.60{col 50}{space 3}0.000{col 58}{space 4}-.0437314{col 71}{space 3}-.0128901
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0178436{col 30}{space 2} .0052853{col 41}{space 1}    3.38{col 50}{space 3}0.001{col 58}{space 4} .0074846{col 71}{space 3} .0282027
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .011126{col 30}{space 2} .0112354{col 41}{space 1}    0.99{col 50}{space 3}0.322{col 58}{space 4} -.010895{col 71}{space 3}  .033147
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0151908{col 30}{space 2} .0493324{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.0814989{col 71}{space 3} .1118805
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1218908{col 30}{space 2} .0187389{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .0851633{col 71}{space 3} .1586184
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1017701{col 30}{space 2} .0256826{col 41}{space 1}    3.96{col 50}{space 3}0.000{col 58}{space 4} .0514332{col 71}{space 3}  .152107
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0512138{col 30}{space 2} .0183935{col 41}{space 1}    2.78{col 50}{space 3}0.005{col 58}{space 4} .0151632{col 71}{space 3} .0872644
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0463322{col 30}{space 2} .0164858{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0140206{col 71}{space 3} .0786438
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} -.005741{col 30}{space 2} .0063229{col 41}{space 1}   -0.91{col 50}{space 3}0.364{col 58}{space 4}-.0181335{col 71}{space 3} .0066516
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0458418{col 30}{space 2} .0095332{col 41}{space 1}    4.81{col 50}{space 3}0.000{col 58}{space 4} .0271571{col 71}{space 3} .0645265
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0191942{col 30}{space 2} .0085025{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0025297{col 71}{space 3} .0358587
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.659897{col 30}{space 2} .0367999{col 41}{space 1}   45.11{col 50}{space 3}0.000{col 58}{space 4}  1.58777{col 71}{space 3} 1.732023
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2}  .036569{col 30}{space 2} .0260468{col 41}{space 1}    1.40{col 50}{space 3}0.160{col 58}{space 4}-.0144817{col 71}{space 3} .0876198
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0154339{col 30}{space 2} .0036584{col 41}{space 1}   -4.22{col 50}{space 3}0.000{col 58}{space 4}-.0226042{col 71}{space 3}-.0082635
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0092608{col 30}{space 2}  .011963{col 41}{space 1}   -0.77{col 50}{space 3}0.439{col 58}{space 4}-.0327079{col 71}{space 3} .0141863
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2541222{col 30}{space 2} .1096239{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4} -.468981{col 71}{space 3}-.0392634
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0013439{col 30}{space 2} .0017887{col 41}{space 1}   -0.75{col 50}{space 3}0.452{col 58}{space 4}-.0048497{col 71}{space 3} .0021618
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0720554{col 30}{space 2}  .065363{col 41}{space 1}   -1.10{col 50}{space 3}0.270{col 58}{space 4}-.2001646{col 71}{space 3} .0560537
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3847435{col 30}{space 2} .0654673{col 41}{space 1}    5.88{col 50}{space 3}0.000{col 58}{space 4} .2564299{col 71}{space 3} .5130571
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2283177{col 30}{space 2} .1662099{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0974478{col 71}{space 3} .5540832
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1102206{col 30}{space 2} .0714739{col 41}{space 1}    1.54{col 50}{space 3}0.123{col 58}{space 4}-.0298657{col 71}{space 3} .2503069
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}   .18022{col 30}{space 2} .1204123{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0557839{col 71}{space 3} .4162238
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1369338{col 30}{space 2} .0791005{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.0181004{col 71}{space 3}  .291968
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2508709{col 30}{space 2} .0556401{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .1418182{col 71}{space 3} .3599235
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1688057{col 30}{space 2} .0469152{col 41}{space 1}   -3.60{col 50}{space 3}0.000{col 58}{space 4}-.2607578{col 71}{space 3}-.0768537
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .1063945{col 30}{space 2}  .031532{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .0445929{col 71}{space 3} .1681961
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0663397{col 30}{space 2} .0669923{col 41}{space 1}    0.99{col 50}{space 3}0.322{col 58}{space 4}-.0649628{col 71}{space 3} .1976423
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0905768{col 30}{space 2} .2941266{col 41}{space 1}    0.31{col 50}{space 3}0.758{col 58}{space 4}-.4859008{col 71}{space 3} .6670544
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7267866{col 30}{space 2} .1118313{col 41}{space 1}    6.50{col 50}{space 3}0.000{col 58}{space 4} .5076013{col 71}{space 3}  .945972
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6068147{col 30}{space 2} .1530516{col 41}{space 1}    3.96{col 50}{space 3}0.000{col 58}{space 4} .3068391{col 71}{space 3} .9067902
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3053676{col 30}{space 2} .1096235{col 41}{space 1}    2.79{col 50}{space 3}0.005{col 58}{space 4} .0905094{col 71}{space 3} .5202257
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2762604{col 30}{space 2} .0983159{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0835648{col 71}{space 3} .4689561
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}-.0342312{col 30}{space 2} .0376885{col 41}{space 1}   -0.91{col 50}{space 3}0.364{col 58}{space 4}-.1080993{col 71}{space 3}  .039637
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2733365{col 30}{space 2} .0567448{col 41}{space 1}    4.82{col 50}{space 3}0.000{col 58}{space 4} .1621188{col 71}{space 3} .3845543
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .1144476{col 30}{space 2} .0506919{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4} .0150934{col 71}{space 3} .2138018
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. poisson hdd9 pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-13050.119}  
Iteration 1:{space 3}log pseudolikelihood = {res:-13050.119}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   1428.17
{txt}Log pseudolikelihood = {res}-13050.119{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0138477{col 30}{space 2} .0051893{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0036769{col 71}{space 3} .0240186
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0002663{col 30}{space 2} .0000617{col 41}{space 1}   -4.32{col 50}{space 3}0.000{col 58}{space 4}-.0003872{col 71}{space 3}-.0001454
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0022507{col 30}{space 2} .0011109{col 41}{space 1}    2.03{col 50}{space 3}0.043{col 58}{space 4} .0000734{col 71}{space 3}  .004428
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0276746{col 30}{space 2} .0178131{col 41}{space 1}   -1.55{col 50}{space 3}0.120{col 58}{space 4}-.0625875{col 71}{space 3} .0072384
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0005447{col 30}{space 2} .0002603{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0000346{col 71}{space 3} .0010548
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0154192{col 30}{space 2} .0105902{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0053371{col 71}{space 3} .0361756
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0620958{col 30}{space 2} .0080174{col 41}{space 1}    7.75{col 50}{space 3}0.000{col 58}{space 4} .0463819{col 71}{space 3} .0778096
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0557224{col 30}{space 2} .0183986{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .0196618{col 71}{space 3} .0917829
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0199738{col 30}{space 2} .0144743{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0083952{col 71}{space 3} .0483429
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0449672{col 30}{space 2} .0205769{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0046372{col 71}{space 3} .0852971
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0361856{col 30}{space 2}   .01561{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0055906{col 71}{space 3} .0667805
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} -.028249{col 30}{space 2} .0127769{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.0532914{col 71}{space 3}-.0032067
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.030362{col 30}{space 2} .0084845{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-.0469914{col 71}{space 3}-.0137326
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0004526{col 30}{space 2}  .000301{col 41}{space 1}   -1.50{col 50}{space 3}0.133{col 58}{space 4}-.0010426{col 71}{space 3} .0001373
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0358409{col 30}{space 2} .0371393{col 41}{space 1}    0.97{col 50}{space 3}0.335{col 58}{space 4}-.0369508{col 71}{space 3} .1086325
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0016265{col 30}{space 2} .0220544{col 41}{space 1}   -0.07{col 50}{space 3}0.941{col 58}{space 4}-.0448523{col 71}{space 3} .0415992
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0569688{col 30}{space 2} .0176978{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .0222819{col 71}{space 3} .0916558
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0786649{col 30}{space 2} .0232222{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .0331502{col 71}{space 3} .1241796
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}   .02785{col 30}{space 2} .0191064{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0095978{col 71}{space 3} .0652977
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .075042{col 30}{space 2} .0155037{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4} .0446552{col 71}{space 3} .1054287
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0102495{col 30}{space 2} .0065403{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0025693{col 71}{space 3} .0230683
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}  .043691{col 30}{space 2}  .007004{col 41}{space 1}    6.24{col 50}{space 3}0.000{col 58}{space 4} .0299634{col 71}{space 3} .0574186
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.418994{col 30}{space 2}  .028252{col 41}{space 1}   50.23{col 50}{space 3}0.000{col 58}{space 4} 1.363621{col 71}{space 3} 1.474367
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0779062{col 30}{space 2} .0291865{col 41}{space 1}    2.67{col 50}{space 3}0.008{col 58}{space 4} .0207018{col 71}{space 3} .1351107
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0014982{col 30}{space 2} .0003475{col 41}{space 1}   -4.31{col 50}{space 3}0.000{col 58}{space 4}-.0021793{col 71}{space 3}-.0008171
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0126622{col 30}{space 2} .0062482{col 41}{space 1}    2.03{col 50}{space 3}0.043{col 58}{space 4} .0004159{col 71}{space 3} .0249084
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.155695{col 30}{space 2} .1002263{col 41}{space 1}   -1.55{col 50}{space 3}0.120{col 58}{space 4}-.3521349{col 71}{space 3} .0407449
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0030644{col 30}{space 2} .0014639{col 41}{space 1}    2.09{col 50}{space 3}0.036{col 58}{space 4} .0001951{col 71}{space 3} .0059336
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0867474{col 30}{space 2} .0595788{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0300248{col 71}{space 3} .2035196
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3493457{col 30}{space 2} .0450396{col 41}{space 1}    7.76{col 50}{space 3}0.000{col 58}{space 4} .2610697{col 71}{space 3} .4376217
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3134896{col 30}{space 2} .1034742{col 41}{space 1}    3.03{col 50}{space 3}0.002{col 58}{space 4} .1106838{col 71}{space 3} .5162953
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1123712{col 30}{space 2} .0814224{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0472138{col 71}{space 3} .2719562
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2529815{col 30}{space 2} .1157487{col 41}{space 1}    2.19{col 50}{space 3}0.029{col 58}{space 4} .0261182{col 71}{space 3} .4798449
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2035772{col 30}{space 2} .0878236{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0314462{col 71}{space 3} .3757082
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1589267{col 30}{space 2} .0718672{col 41}{space 1}   -2.21{col 50}{space 3}0.027{col 58}{space 4}-.2997839{col 71}{space 3}-.0180696
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.170814{col 30}{space 2} .0477503{col 41}{space 1}   -3.58{col 50}{space 3}0.000{col 58}{space 4}-.2644029{col 71}{space 3}-.0772252
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0025465{col 30}{space 2} .0016935{col 41}{space 1}   -1.50{col 50}{space 3}0.133{col 58}{space 4}-.0058658{col 71}{space 3} .0007728
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2016378{col 30}{space 2} .2089421{col 41}{space 1}    0.97{col 50}{space 3}0.335{col 58}{space 4}-.2078812{col 71}{space 3} .6111567
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0091506{col 30}{space 2} .1240754{col 41}{space 1}   -0.07{col 50}{space 3}0.941{col 58}{space 4}-.2523339{col 71}{space 3} .2340327
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .320502{col 30}{space 2} .0995619{col 41}{space 1}    3.22{col 50}{space 3}0.001{col 58}{space 4} .1253643{col 71}{space 3} .5156398
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4425622{col 30}{space 2} .1306228{col 41}{space 1}    3.39{col 50}{space 3}0.001{col 58}{space 4} .1865462{col 71}{space 3} .6985783
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1566816{col 30}{space 2} .1074836{col 41}{space 1}    1.46{col 50}{space 3}0.145{col 58}{space 4}-.0539823{col 71}{space 3} .3673454
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4221799{col 30}{space 2} .0871546{col 41}{space 1}    4.84{col 50}{space 3}0.000{col 58}{space 4}   .25136{col 71}{space 3} .5929998
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0576626{col 30}{space 2} .0367994{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0144628{col 71}{space 3} .1297881
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2458019{col 30}{space 2} .0393003{col 41}{space 1}    6.25{col 50}{space 3}0.000{col 58}{space 4} .1687747{col 71}{space 3} .3228291
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-29969.165}  
Iteration 1:{space 3}log pseudolikelihood = {res:-29969.165}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   4054.45
{txt}Log pseudolikelihood = {res}-29969.165{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0118761{col 30}{space 2} .0026101{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0067604{col 71}{space 3} .0169917
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0036901{col 30}{space 2} .0004425{col 41}{space 1}   -8.34{col 50}{space 3}0.000{col 58}{space 4}-.0045573{col 71}{space 3}-.0028228
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0039109{col 30}{space 2} .0008346{col 41}{space 1}   -4.69{col 50}{space 3}0.000{col 58}{space 4}-.0055467{col 71}{space 3}-.0022751
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0262999{col 30}{space 2} .0094827{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4} .0077141{col 71}{space 3} .0448857
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0007473{col 30}{space 2} .0001712{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0004116{col 71}{space 3} .0010829
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0590697{col 30}{space 2} .0066509{col 41}{space 1}    8.88{col 50}{space 3}0.000{col 58}{space 4} .0460343{col 71}{space 3} .0721052
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0402126{col 30}{space 2} .0052925{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} .0298396{col 71}{space 3} .0505856
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0029138{col 30}{space 2}  .007292{col 41}{space 1}    0.40{col 50}{space 3}0.689{col 58}{space 4}-.0113782{col 71}{space 3} .0172058
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0330521{col 30}{space 2} .0075612{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .0182324{col 71}{space 3} .0478718
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0121568{col 30}{space 2} .0084002{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0043073{col 71}{space 3} .0286209
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0403582{col 30}{space 2} .0093088{col 41}{space 1}    4.34{col 50}{space 3}0.000{col 58}{space 4} .0221133{col 71}{space 3} .0586031
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0545595{col 30}{space 2} .0076389{col 41}{space 1}    7.14{col 50}{space 3}0.000{col 58}{space 4} .0395876{col 71}{space 3} .0695313
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0061447{col 30}{space 2} .0086229{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4} -.010756{col 71}{space 3} .0230453
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0018223{col 30}{space 2} .0014273{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0046198{col 71}{space 3} .0009753
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0654406{col 30}{space 2} .0099939{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4} .0458529{col 71}{space 3} .0850283
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .013574{col 30}{space 2}  .009658{col 41}{space 1}    1.41{col 50}{space 3}0.160{col 58}{space 4}-.0053553{col 71}{space 3} .0325032
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1408741{col 30}{space 2} .0109795{col 41}{space 1}   12.83{col 50}{space 3}0.000{col 58}{space 4} .1193547{col 71}{space 3} .1623935
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1312215{col 30}{space 2} .0103479{col 41}{space 1}   12.68{col 50}{space 3}0.000{col 58}{space 4} .1109401{col 71}{space 3}  .151503
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0243103{col 30}{space 2} .0119582{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0008726{col 71}{space 3}  .047748
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0127225{col 30}{space 2} .0096149{col 41}{space 1}   -1.32{col 50}{space 3}0.186{col 58}{space 4}-.0315674{col 71}{space 3} .0061225
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0204797{col 30}{space 2} .0033101{col 41}{space 1}    6.19{col 50}{space 3}0.000{col 58}{space 4}  .013992{col 71}{space 3} .0269674
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0907938{col 30}{space 2} .0058751{col 41}{space 1}  -15.45{col 50}{space 3}0.000{col 58}{space 4}-.1023087{col 71}{space 3}-.0792789
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0841251{col 30}{space 2} .0059541{col 41}{space 1}  -14.13{col 50}{space 3}0.000{col 58}{space 4}-.0957949{col 71}{space 3}-.0724553
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0599883{col 30}{space 2}  .005892{col 41}{space 1}  -10.18{col 50}{space 3}0.000{col 58}{space 4}-.0715363{col 71}{space 3}-.0484402
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.411155{col 30}{space 2} .0167789{col 41}{space 1}   84.10{col 50}{space 3}0.000{col 58}{space 4} 1.378269{col 71}{space 3} 1.444041
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0691378{col 30}{space 2} .0151926{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0393609{col 71}{space 3} .0989148
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0214822{col 30}{space 2} .0025771{col 41}{space 1}   -8.34{col 50}{space 3}0.000{col 58}{space 4}-.0265332{col 71}{space 3}-.0164313
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0227679{col 30}{space 2} .0048609{col 41}{space 1}   -4.68{col 50}{space 3}0.000{col 58}{space 4}-.0322952{col 71}{space 3}-.0132407
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}  .153108{col 30}{space 2}  .055201{col 41}{space 1}    2.77{col 50}{space 3}0.006{col 58}{space 4}  .044916{col 71}{space 3} .2613001
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0043503{col 30}{space 2} .0009967{col 41}{space 1}    4.36{col 50}{space 3}0.000{col 58}{space 4} .0023968{col 71}{space 3} .0063037
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .3438812{col 30}{space 2} .0386725{col 41}{space 1}    8.89{col 50}{space 3}0.000{col 58}{space 4} .2680845{col 71}{space 3} .4196779
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2341024{col 30}{space 2} .0308099{col 41}{space 1}    7.60{col 50}{space 3}0.000{col 58}{space 4} .1737162{col 71}{space 3} .2944887
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0169632{col 30}{space 2} .0424511{col 41}{space 1}    0.40{col 50}{space 3}0.689{col 58}{space 4}-.0662394{col 71}{space 3} .1001659
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1924168{col 30}{space 2} .0440088{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .1061612{col 71}{space 3} .2786724
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0707722{col 30}{space 2} .0489016{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0250731{col 71}{space 3} .1666175
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2349499{col 30}{space 2} .0541759{col 41}{space 1}    4.34{col 50}{space 3}0.000{col 58}{space 4} .1287672{col 71}{space 3} .3411326
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3176242{col 30}{space 2} .0444672{col 41}{space 1}    7.14{col 50}{space 3}0.000{col 58}{space 4} .2304701{col 71}{space 3} .4047783
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0357718{col 30}{space 2} .0501983{col 41}{space 1}    0.71{col 50}{space 3}0.476{col 58}{space 4}-.0626151{col 71}{space 3} .1341588
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0106085{col 30}{space 2} .0083093{col 41}{space 1}   -1.28{col 50}{space 3}0.202{col 58}{space 4}-.0268944{col 71}{space 3} .0056773
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3809699{col 30}{space 2} .0581801{col 41}{space 1}    6.55{col 50}{space 3}0.000{col 58}{space 4}  .266939{col 71}{space 3} .4950009
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0790225{col 30}{space 2} .0562261{col 41}{space 1}    1.41{col 50}{space 3}0.160{col 58}{space 4}-.0311786{col 71}{space 3} .1892237
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .8201149{col 30}{space 2} .0639195{col 41}{space 1}   12.83{col 50}{space 3}0.000{col 58}{space 4} .6948349{col 71}{space 3} .9453948
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7639214{col 30}{space 2}  .060247{col 41}{space 1}   12.68{col 50}{space 3}0.000{col 58}{space 4} .6458396{col 71}{space 3} .8820033
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1415253{col 30}{space 2} .0696211{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .0050704{col 71}{space 3} .2779802
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.0740653{col 30}{space 2} .0559769{col 41}{space 1}   -1.32{col 50}{space 3}0.186{col 58}{space 4}-.1837779{col 71}{space 3} .0356474
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .119225{col 30}{space 2} .0192619{col 41}{space 1}    6.19{col 50}{space 3}0.000{col 58}{space 4} .0814723{col 71}{space 3} .1569777
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5285667{col 30}{space 2}  .034117{col 41}{space 1}  -15.49{col 50}{space 3}0.000{col 58}{space 4}-.5954348{col 71}{space 3}-.4616986
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.4897439{col 30}{space 2} .0345278{col 41}{space 1}  -14.18{col 50}{space 3}0.000{col 58}{space 4} -.557417{col 71}{space 3}-.4220707
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3492287{col 30}{space 2} .0342256{col 41}{space 1}  -10.20{col 50}{space 3}0.000{col 58}{space 4}-.4163096{col 71}{space 3}-.2821477
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_TANZANIA if country==5, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23410.515}  
Iteration 1:{space 3}log pseudolikelihood = {res:-23410.515}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   1916.18
{txt}Log pseudolikelihood = {res}-23410.515{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0005588{col 30}{space 2} .0036502{col 41}{space 1}    0.15{col 50}{space 3}0.878{col 58}{space 4}-.0065954{col 71}{space 3} .0077131
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2} -.003202{col 30}{space 2} .0008534{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.0048747{col 71}{space 3}-.0015293
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0006678{col 30}{space 2}  .001001{col 41}{space 1}   -0.67{col 50}{space 3}0.505{col 58}{space 4}-.0026297{col 71}{space 3} .0012941
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0057235{col 30}{space 2} .0122114{col 41}{space 1}   -0.47{col 50}{space 3}0.639{col 58}{space 4}-.0296574{col 71}{space 3} .0182104
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0001129{col 30}{space 2} .0001905{col 41}{space 1}   -0.59{col 50}{space 3}0.553{col 58}{space 4}-.0004862{col 71}{space 3} .0002604
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0060962{col 30}{space 2}  .006749{col 41}{space 1}    0.90{col 50}{space 3}0.366{col 58}{space 4}-.0071316{col 71}{space 3} .0193239
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0564496{col 30}{space 2} .0067234{col 41}{space 1}    8.40{col 50}{space 3}0.000{col 58}{space 4}  .043272{col 71}{space 3} .0696271
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0410724{col 30}{space 2} .0136308{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4} .0143566{col 71}{space 3} .0677883
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0514838{col 30}{space 2} .0089614{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .0339197{col 71}{space 3}  .069048
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0003139{col 30}{space 2}   .00951{col 41}{space 1}   -0.03{col 50}{space 3}0.974{col 58}{space 4}-.0189532{col 71}{space 3} .0183254
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0252352{col 30}{space 2} .0068853{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0117403{col 71}{space 3}   .03873
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0422834{col 30}{space 2}  .007148{col 41}{space 1}    5.92{col 50}{space 3}0.000{col 58}{space 4} .0282735{col 71}{space 3} .0562933
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.03378{col 30}{space 2} .0062645{col 41}{space 1}   -5.39{col 50}{space 3}0.000{col 58}{space 4}-.0460582{col 71}{space 3}-.0215018
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0003483{col 30}{space 2} .0005997{col 41}{space 1}    0.58{col 50}{space 3}0.561{col 58}{space 4} -.000827{col 71}{space 3} .0015236
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0308468{col 30}{space 2} .0058831{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0193162{col 71}{space 3} .0423774
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0415073{col 30}{space 2} .0178752{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0064726{col 71}{space 3} .0765421
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0820619{col 30}{space 2} .0122483{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .0580557{col 71}{space 3} .1060681
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0952621{col 30}{space 2} .0124593{col 41}{space 1}    7.65{col 50}{space 3}0.000{col 58}{space 4} .0708424{col 71}{space 3} .1196818
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0058621{col 30}{space 2} .0098027{col 41}{space 1}   -0.60{col 50}{space 3}0.550{col 58}{space 4} -.025075{col 71}{space 3} .0133507
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0391662{col 30}{space 2}  .010035{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4}  .019498{col 71}{space 3} .0588345
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0034936{col 30}{space 2} .0043462{col 41}{space 1}    0.80{col 50}{space 3}0.421{col 58}{space 4}-.0050247{col 71}{space 3}  .012012
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0178407{col 30}{space 2} .0070503{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4} .0040222{col 71}{space 3} .0316591
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .0228828{col 30}{space 2} .0059997{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .0111236{col 71}{space 3} .0346421
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0000223{col 30}{space 2} .0062364{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.0122454{col 71}{space 3} .0122007
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.538059{col 30}{space 2}    .0207{col 41}{space 1}   74.30{col 50}{space 3}0.000{col 58}{space 4} 1.497488{col 71}{space 3}  1.57863
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0031972{col 30}{space 2} .0208842{col 41}{space 1}    0.15{col 50}{space 3}0.878{col 58}{space 4} -.037735{col 71}{space 3} .0441294
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0183197{col 30}{space 2} .0048845{col 41}{space 1}   -3.75{col 50}{space 3}0.000{col 58}{space 4}-.0278932{col 71}{space 3}-.0087463
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0038206{col 30}{space 2} .0057275{col 41}{space 1}   -0.67{col 50}{space 3}0.505{col 58}{space 4}-.0150462{col 71}{space 3} .0074051
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0327464{col 30}{space 2} .0698692{col 41}{space 1}   -0.47{col 50}{space 3}0.639{col 58}{space 4}-.1696874{col 71}{space 3} .1041947
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000646{col 30}{space 2} .0010896{col 41}{space 1}   -0.59{col 50}{space 3}0.553{col 58}{space 4}-.0027816{col 71}{space 3} .0014897
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0348785{col 30}{space 2}  .038616{col 41}{space 1}    0.90{col 50}{space 3}0.366{col 58}{space 4}-.0408074{col 71}{space 3} .1105645
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3229698{col 30}{space 2} .0384852{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .2475401{col 71}{space 3} .3983994
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2349912{col 30}{space 2} .0779806{col 41}{space 1}    3.01{col 50}{space 3}0.003{col 58}{space 4}  .082152{col 71}{space 3} .3878304
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .294559{col 30}{space 2} .0512677{col 41}{space 1}    5.75{col 50}{space 3}0.000{col 58}{space 4} .1940761{col 71}{space 3} .3950419
{txt}{space 5}electricity {c |}{col 18}{res}{space 2}-.0017959{col 30}{space 2} .0544107{col 41}{space 1}   -0.03{col 50}{space 3}0.974{col 58}{space 4}-.1084389{col 71}{space 3}  .104847
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1443801{col 30}{space 2} .0393836{col 41}{space 1}    3.67{col 50}{space 3}0.000{col 58}{space 4} .0671897{col 71}{space 3} .2215704
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2419195{col 30}{space 2} .0409004{col 41}{space 1}    5.91{col 50}{space 3}0.000{col 58}{space 4} .1617561{col 71}{space 3} .3220829
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1932687{col 30}{space 2} .0358434{col 41}{space 1}   -5.39{col 50}{space 3}0.000{col 58}{space 4}-.2635204{col 71}{space 3}-.1230169
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0019929{col 30}{space 2} .0034308{col 41}{space 1}    0.58{col 50}{space 3}0.561{col 58}{space 4}-.0047314{col 71}{space 3} .0087172
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1764865{col 30}{space 2} .0336567{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .1105206{col 71}{space 3} .2424524
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2374794{col 30}{space 2} .1022821{col 41}{space 1}    2.32{col 50}{space 3}0.020{col 58}{space 4} .0370103{col 71}{space 3} .4379486
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4695078{col 30}{space 2} .0700806{col 41}{space 1}    6.70{col 50}{space 3}0.000{col 58}{space 4} .3321523{col 71}{space 3} .6068633
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5450312{col 30}{space 2} .0712527{col 41}{space 1}    7.65{col 50}{space 3}0.000{col 58}{space 4} .4053784{col 71}{space 3}  .684684
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0335396{col 30}{space 2}  .056083{col 41}{space 1}   -0.60{col 50}{space 3}0.550{col 58}{space 4}-.1434602{col 71}{space 3}  .076381
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2240852{col 30}{space 2} .0573929{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .1115971{col 71}{space 3} .3365733
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0199885{col 30}{space 2} .0248686{col 41}{space 1}    0.80{col 50}{space 3}0.422{col 58}{space 4} -.028753{col 71}{space 3}   .06873
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .1020734{col 30}{space 2} .0403525{col 41}{space 1}    2.53{col 50}{space 3}0.011{col 58}{space 4}  .022984{col 71}{space 3} .1811627
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .1309214{col 30}{space 2} .0343264{col 41}{space 1}    3.81{col 50}{space 3}0.000{col 58}{space 4} .0636428{col 71}{space 3}    .1982
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2}-.0001278{col 30}{space 2} .0356808{col 41}{space 1}   -0.00{col 50}{space 3}0.997{col 58}{space 4}-.0700608{col 71}{space 3} .0698051
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9  pdd9_town sum_town  $xlist  pdd9_mean_town $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-31891.423}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31891.423}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 49}Wald chi2({res}26{txt}){col 67}= {res}   2379.82
{txt}Log pseudolikelihood = {res}-31891.423{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0036259{col 30}{space 2} .0025053{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0012844{col 71}{space 3} .0085363
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0039551{col 30}{space 2} .0005832{col 41}{space 1}   -6.78{col 50}{space 3}0.000{col 58}{space 4}-.0050982{col 71}{space 3}-.0028121
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0044914{col 30}{space 2} .0009876{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0025556{col 71}{space 3} .0064271
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0027966{col 30}{space 2} .0117994{col 41}{space 1}    0.24{col 50}{space 3}0.813{col 58}{space 4}-.0203299{col 71}{space 3}  .025923
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0002621{col 30}{space 2} .0001897{col 41}{space 1}   -1.38{col 50}{space 3}0.167{col 58}{space 4}-.0006339{col 71}{space 3} .0001098
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0071602{col 30}{space 2} .0064472{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-.0054761{col 71}{space 3} .0197965
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .070617{col 30}{space 2} .0065889{col 41}{space 1}   10.72{col 50}{space 3}0.000{col 58}{space 4} .0577029{col 71}{space 3} .0835311
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0354732{col 30}{space 2} .0091867{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4} .0174675{col 71}{space 3} .0534789
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0472257{col 30}{space 2} .0070277{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .0334517{col 71}{space 3} .0609997
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0561088{col 30}{space 2} .0064862{col 41}{space 1}    8.65{col 50}{space 3}0.000{col 58}{space 4}  .043396{col 71}{space 3} .0688216
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0060752{col 30}{space 2} .0054736{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-.0046529{col 71}{space 3} .0168032
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0361401{col 30}{space 2} .0057224{col 41}{space 1}    6.32{col 50}{space 3}0.000{col 58}{space 4} .0249244{col 71}{space 3} .0473558
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0065965{col 30}{space 2} .0049511{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.0163006{col 71}{space 3} .0031075
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0005524{col 30}{space 2} .0003676{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0001681{col 71}{space 3} .0012729
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0062111{col 30}{space 2} .0054175{col 41}{space 1}    1.15{col 50}{space 3}0.252{col 58}{space 4} -.004407{col 71}{space 3} .0168291
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0157649{col 30}{space 2} .0140113{col 41}{space 1}    1.13{col 50}{space 3}0.261{col 58}{space 4}-.0116968{col 71}{space 3} .0432265
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0618223{col 30}{space 2} .0116386{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4} .0390112{col 71}{space 3} .0846335
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0584867{col 30}{space 2} .0115867{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .0357772{col 71}{space 3} .0811962
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .015742{col 30}{space 2} .0098942{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.0036503{col 71}{space 3} .0351343
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0528752{col 30}{space 2} .0095977{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4}  .034064{col 71}{space 3} .0716865
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2} .0364087{col 30}{space 2} .0041322{col 41}{space 1}    8.81{col 50}{space 3}0.000{col 58}{space 4} .0283098{col 71}{space 3} .0445076
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0293021{col 30}{space 2} .0074818{col 41}{space 1}   -3.92{col 50}{space 3}0.000{col 58}{space 4}-.0439663{col 71}{space 3} -.014638
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0169389{col 30}{space 2}   .00642{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.0295218{col 71}{space 3}-.0043559
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0630869{col 30}{space 2} .0061879{col 41}{space 1}   10.20{col 50}{space 3}0.000{col 58}{space 4} .0509588{col 71}{space 3} .0752149
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0211958{col 30}{space 2} .0062965{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .0088549{col 71}{space 3} .0335368
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0535873{col 30}{space 2} .0057193{col 41}{space 1}    9.37{col 50}{space 3}0.000{col 58}{space 4} .0423777{col 71}{space 3} .0647968
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.276018{col 30}{space 2} .0245921{col 41}{space 1}   51.89{col 50}{space 3}0.000{col 58}{space 4} 1.227819{col 71}{space 3} 1.324218
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_town sum_town hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_town year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_town {c |}{col 18}{res}{space 2} .0202665{col 30}{space 2} .0140028{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0071786{col 71}{space 3} .0477116
{txt}{space 8}sum_town {c |}{col 18}{res}{space 2}-.0221065{col 30}{space 2} .0032567{col 41}{space 1}   -6.79{col 50}{space 3}0.000{col 58}{space 4}-.0284895{col 71}{space 3}-.0157235
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0251035{col 30}{space 2} .0055187{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4}  .014287{col 71}{space 3} .0359201
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0156308{col 30}{space 2}   .06595{col 41}{space 1}    0.24{col 50}{space 3}0.813{col 58}{space 4}-.1136288{col 71}{space 3} .1448903
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014649{col 30}{space 2} .0010604{col 41}{space 1}   -1.38{col 50}{space 3}0.167{col 58}{space 4}-.0035432{col 71}{space 3} .0006135
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0400205{col 30}{space 2} .0360342{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4}-.0306054{col 71}{space 3} .1106463
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3946996{col 30}{space 2} .0368041{col 41}{space 1}   10.72{col 50}{space 3}0.000{col 58}{space 4} .3225649{col 71}{space 3} .4668343
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1982703{col 30}{space 2} .0513389{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4} .0976479{col 71}{space 3} .2988928
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2639586{col 30}{space 2} .0392548{col 41}{space 1}    6.72{col 50}{space 3}0.000{col 58}{space 4} .1870207{col 71}{space 3} .3408966
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3136088{col 30}{space 2} .0362473{col 41}{space 1}    8.65{col 50}{space 3}0.000{col 58}{space 4} .2425655{col 71}{space 3} .3846522
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .033956{col 30}{space 2} .0305975{col 41}{space 1}    1.11{col 50}{space 3}0.267{col 58}{space 4} -.026014{col 71}{space 3} .0939261
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2019979{col 30}{space 2} .0319956{col 41}{space 1}    6.31{col 50}{space 3}0.000{col 58}{space 4} .1392877{col 71}{space 3} .2647082
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}  -.03687{col 30}{space 2} .0276747{col 41}{space 1}   -1.33{col 50}{space 3}0.183{col 58}{space 4}-.0911115{col 71}{space 3} .0173715
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0030875{col 30}{space 2} .0020548{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0009399{col 71}{space 3} .0071149
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0347156{col 30}{space 2} .0302812{col 41}{space 1}    1.15{col 50}{space 3}0.252{col 58}{space 4}-.0246344{col 71}{space 3} .0940656
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0881146{col 30}{space 2} .0783146{col 41}{space 1}    1.13{col 50}{space 3}0.261{col 58}{space 4}-.0653792{col 71}{space 3} .2416084
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3455436{col 30}{space 2} .0650151{col 41}{space 1}    5.31{col 50}{space 3}0.000{col 58}{space 4} .2181163{col 71}{space 3} .4729708
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3268997{col 30}{space 2} .0647084{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .2000736{col 71}{space 3} .4537258
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .087987{col 30}{space 2} .0553071{col 41}{space 1}    1.59{col 50}{space 3}0.112{col 58}{space 4}-.0204129{col 71}{space 3} .1963869
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2955357{col 30}{space 2} .0536482{col 41}{space 1}    5.51{col 50}{space 3}0.000{col 58}{space 4} .1903871{col 71}{space 3} .4006842
{txt}{space 2}pdd9_mean_town {c |}{col 18}{res}{space 2}  .203499{col 30}{space 2} .0230492{col 41}{space 1}    8.83{col 50}{space 3}0.000{col 58}{space 4} .1583234{col 71}{space 3} .2486746
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1637785{col 30}{space 2} .0417916{col 41}{space 1}   -3.92{col 50}{space 3}0.000{col 58}{space 4}-.2456885{col 71}{space 3}-.0818685
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0946764{col 30}{space 2} .0358913{col 41}{space 1}   -2.64{col 50}{space 3}0.008{col 58}{space 4}-.1650221{col 71}{space 3}-.0243307
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .3526114{col 30}{space 2} .0345615{col 41}{space 1}   10.20{col 50}{space 3}0.000{col 58}{space 4} .2848722{col 71}{space 3} .4203506
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}   .11847{col 30}{space 2} .0351879{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4}  .049503{col 71}{space 3} .1874369
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2995155{col 30}{space 2} .0319787{col 41}{space 1}    9.37{col 50}{space 3}0.000{col 58}{space 4} .2368384{col 71}{space 3} .3621925
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S26_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_town    $xlist  pdd9_mean_town sum_town  )
{res}{txt}(note: file S26_poisson.rtf not found)
(output written to {browse  `"S26_poisson.rtf"'})

{com}. 
. 
. 
. ********************************************************************************
. *                                   S27                                        *
. ********************************************************************************
. *                          dist_village_level                                  *
. 
. eststo clear
{txt}
{com}. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist i.country i.year   , cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-128856.17}  
Iteration 1:{space 3}log pseudolikelihood = {res:-128856.16}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 49}Wald chi2({res}36{txt}){col 67}= {res}  17980.19
{txt}Log pseudolikelihood = {res}-128856.16{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:27,229} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}  .005734{col 30}{space 2} .0017101{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0023823{col 71}{space 3} .0090856
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0002483{col 30}{space 2} .0000317{col 41}{space 1}   -7.82{col 50}{space 3}0.000{col 58}{space 4}-.0003105{col 71}{space 3}-.0001861
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0000971{col 30}{space 2} .0004558{col 41}{space 1}   -0.21{col 50}{space 3}0.831{col 58}{space 4}-.0009904{col 71}{space 3} .0007962
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0023486{col 30}{space 2} .0054365{col 41}{space 1}    0.43{col 50}{space 3}0.666{col 58}{space 4}-.0083068{col 71}{space 3}  .013004
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0001541{col 30}{space 2} .0000887{col 41}{space 1}    1.74{col 50}{space 3}0.083{col 58}{space 4}-.0000199{col 71}{space 3}  .000328
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0116101{col 30}{space 2} .0032634{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .0052139{col 71}{space 3} .0180063
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .066585{col 30}{space 2} .0029291{col 41}{space 1}   22.73{col 50}{space 3}0.000{col 58}{space 4}  .060844{col 71}{space 3} .0723259
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0204972{col 30}{space 2} .0049699{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .0107563{col 71}{space 3} .0302381
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0350609{col 30}{space 2} .0037078{col 41}{space 1}    9.46{col 50}{space 3}0.000{col 58}{space 4} .0277937{col 71}{space 3} .0423281
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0266704{col 30}{space 2}  .004052{col 41}{space 1}    6.58{col 50}{space 3}0.000{col 58}{space 4} .0187287{col 71}{space 3} .0346122
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0232052{col 30}{space 2} .0035345{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .0162778{col 71}{space 3} .0301326
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0393337{col 30}{space 2} .0033182{col 41}{space 1}   11.85{col 50}{space 3}0.000{col 58}{space 4} .0328302{col 71}{space 3} .0458371
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} -.020095{col 30}{space 2} .0028558{col 41}{space 1}   -7.04{col 50}{space 3}0.000{col 58}{space 4}-.0256923{col 71}{space 3}-.0144977
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} 1.51e-06{col 30}{space 2} .0002093{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-.0004088{col 71}{space 3} .0004118
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0388828{col 30}{space 2}   .00315{col 41}{space 1}   12.34{col 50}{space 3}0.000{col 58}{space 4} .0327089{col 71}{space 3} .0450568
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0032852{col 30}{space 2}   .00665{col 41}{space 1}    0.49{col 50}{space 3}0.621{col 58}{space 4}-.0097486{col 71}{space 3}  .016319
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1087948{col 30}{space 2} .0054174{col 41}{space 1}   20.08{col 50}{space 3}0.000{col 58}{space 4} .0981768{col 71}{space 3} .1194128
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1087324{col 30}{space 2} .0054224{col 41}{space 1}   20.05{col 50}{space 3}0.000{col 58}{space 4} .0981047{col 71}{space 3} .1193602
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0200307{col 30}{space 2} .0051777{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0098825{col 71}{space 3} .0301789
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  .024817{col 30}{space 2} .0046794{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .0156456{col 71}{space 3} .0339884
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0137181{col 30}{space 2} .0022704{col 41}{space 1}    6.04{col 50}{space 3}0.000{col 58}{space 4} .0092682{col 71}{space 3}  .018168
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2} -.101826{col 30}{space 2}  .006167{col 41}{space 1}  -16.51{col 50}{space 3}0.000{col 58}{space 4}-.1139131{col 71}{space 3}-.0897389
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-.3267536{col 30}{space 2} .0073089{col 41}{space 1}  -44.71{col 50}{space 3}0.000{col 58}{space 4}-.3410787{col 71}{space 3}-.3124285
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.1164042{col 30}{space 2} .0069039{col 41}{space 1}  -16.86{col 50}{space 3}0.000{col 58}{space 4}-.1299356{col 71}{space 3}-.1028728
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.0811454{col 30}{space 2} .0068004{col 41}{space 1}  -11.93{col 50}{space 3}0.000{col 58}{space 4} -.094474{col 71}{space 3}-.0678169
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .0393163{col 30}{space 2}  .007822{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .0239854{col 71}{space 3} .0546472
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.0562875{col 30}{space 2} .0089485{col 41}{space 1}   -6.29{col 50}{space 3}0.000{col 58}{space 4}-.0738263{col 71}{space 3}-.0387488
{txt}{space 11}2010  {c |}{col 18}{res}{space 2} -.004862{col 30}{space 2} .0065592{col 41}{space 1}   -0.74{col 50}{space 3}0.459{col 58}{space 4}-.0177179{col 71}{space 3} .0079938
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0146641{col 30}{space 2} .0073925{col 41}{space 1}   -1.98{col 50}{space 3}0.047{col 58}{space 4} -.029153{col 71}{space 3}-.0001751
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0029707{col 30}{space 2} .0066278{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.0159609{col 71}{space 3} .0100195
{txt}{space 11}2013  {c |}{col 18}{res}{space 2}  .010806{col 30}{space 2} .0074046{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0037068{col 71}{space 3} .0253187
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.0385532{col 30}{space 2} .0073706{col 41}{space 1}   -5.23{col 50}{space 3}0.000{col 58}{space 4}-.0529994{col 71}{space 3} -.024107
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .0224427{col 30}{space 2} .0071117{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4}  .008504{col 71}{space 3} .0363815
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.0485874{col 30}{space 2} .0105051{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4}-.0691771{col 71}{space 3}-.0279977
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .0632313{col 30}{space 2}  .007392{col 41}{space 1}    8.55{col 50}{space 3}0.000{col 58}{space 4} .0487432{col 71}{space 3} .0777193
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.0226361{col 30}{space 2} .0072532{col 41}{space 1}   -3.12{col 50}{space 3}0.002{col 58}{space 4}-.0368521{col 71}{space 3}  -.00842
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} 1.459494{col 30}{space 2} .0140904{col 41}{space 1}  103.58{col 50}{space 3}0.000{col 58}{space 4} 1.431878{col 71}{space 3} 1.487111
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    65,579
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist 2.country 3.country 4.country 5.country 6.country 2009.year 2010.year 2011.year 2012.year 2013.year 2014.year 2015.year 2016.year 2018.year 2019.year}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0313074{col 30}{space 2} .0093369{col 41}{space 1}    3.35{col 50}{space 3}0.001{col 58}{space 4} .0130074{col 71}{space 3} .0496075
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0013557{col 30}{space 2} .0001733{col 41}{space 1}   -7.82{col 50}{space 3}0.000{col 58}{space 4}-.0016953{col 71}{space 3} -.001016
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0005302{col 30}{space 2} .0024884{col 41}{space 1}   -0.21{col 50}{space 3}0.831{col 58}{space 4}-.0054075{col 71}{space 3}  .004347
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0128235{col 30}{space 2} .0296832{col 41}{space 1}    0.43{col 50}{space 3}0.666{col 58}{space 4}-.0453545{col 71}{space 3} .0710015
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0008413{col 30}{space 2} .0004845{col 41}{space 1}    1.74{col 50}{space 3}0.083{col 58}{space 4}-.0001084{col 71}{space 3} .0017909
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0633913{col 30}{space 2} .0178192{col 41}{space 1}    3.56{col 50}{space 3}0.000{col 58}{space 4} .0284663{col 71}{space 3} .0983162
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3635535{col 30}{space 2}  .015992{col 41}{space 1}   22.73{col 50}{space 3}0.000{col 58}{space 4} .3322098{col 71}{space 3} .3948972
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1119146{col 30}{space 2} .0271352{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .0587306{col 71}{space 3} .1650987
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1914323{col 30}{space 2} .0202423{col 41}{space 1}    9.46{col 50}{space 3}0.000{col 58}{space 4} .1517581{col 71}{space 3} .2311065
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1456204{col 30}{space 2} .0221227{col 41}{space 1}    6.58{col 50}{space 3}0.000{col 58}{space 4} .1022607{col 71}{space 3} .1889802
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1267002{col 30}{space 2} .0192983{col 41}{space 1}    6.57{col 50}{space 3}0.000{col 58}{space 4} .0888762{col 71}{space 3} .1645243
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2147616{col 30}{space 2} .0181173{col 41}{space 1}   11.85{col 50}{space 3}0.000{col 58}{space 4} .1792522{col 71}{space 3} .2502709
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1097186{col 30}{space 2} .0155935{col 41}{space 1}   -7.04{col 50}{space 3}0.000{col 58}{space 4}-.1402813{col 71}{space 3}-.0791559
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} 8.25e-06{col 30}{space 2} .0011429{col 41}{space 1}    0.01{col 50}{space 3}0.994{col 58}{space 4}-.0022318{col 71}{space 3} .0022483
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .2123002{col 30}{space 2} .0172003{col 41}{space 1}   12.34{col 50}{space 3}0.000{col 58}{space 4} .1785882{col 71}{space 3} .2460121
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0179372{col 30}{space 2} .0363091{col 41}{space 1}    0.49{col 50}{space 3}0.621{col 58}{space 4}-.0532274{col 71}{space 3} .0891017
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .594019{col 30}{space 2} .0295607{col 41}{space 1}   20.09{col 50}{space 3}0.000{col 58}{space 4} .5360811{col 71}{space 3}  .651957
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5936786{col 30}{space 2} .0295876{col 41}{space 1}   20.07{col 50}{space 3}0.000{col 58}{space 4} .5356879{col 71}{space 3} .6516693
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1093673{col 30}{space 2} .0282717{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0539559{col 71}{space 3} .1647788
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .1355007{col 30}{space 2} .0255474{col 41}{space 1}    5.30{col 50}{space 3}0.000{col 58}{space 4} .0854286{col 71}{space 3} .1855727
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0749008{col 30}{space 2} .0123944{col 41}{space 1}    6.04{col 50}{space 3}0.000{col 58}{space 4} .0506081{col 71}{space 3} .0991935
{txt}{space 16} {c |}
{space 9}country {c |}
{space 8}Nigeria  {c |}{col 18}{res}{space 2}-.5933041{col 30}{space 2} .0368593{col 41}{space 1}  -16.10{col 50}{space 3}0.000{col 58}{space 4}-.6655471{col 71}{space 3}-.5210612
{txt}{space 7}Ethiopia  {c |}{col 18}{res}{space 2}-1.708203{col 30}{space 2} .0402199{col 41}{space 1}  -42.47{col 50}{space 3}0.000{col 58}{space 4}-1.787033{col 71}{space 3}-1.629373
{txt}{space 9}Uganda  {c |}{col 18}{res}{space 2}-.6734097{col 30}{space 2} .0409642{col 41}{space 1}  -16.44{col 50}{space 3}0.000{col 58}{space 4}-.7536981{col 71}{space 3}-.5931212
{txt}{space 7}Tanzania  {c |}{col 18}{res}{space 2}-.4776448{col 30}{space 2} .0407005{col 41}{space 1}  -11.74{col 50}{space 3}0.000{col 58}{space 4}-.5574164{col 71}{space 3}-.3978733
{txt}{space 9}Malawi  {c |}{col 18}{res}{space 2} .2457427{col 30}{space 2} .0488443{col 41}{space 1}    5.03{col 50}{space 3}0.000{col 58}{space 4} .1500097{col 71}{space 3} .3414757
{txt}{space 16} {c |}
{space 12}year {c |}
{space 11}2009  {c |}{col 18}{res}{space 2}-.2988767{col 30}{space 2} .0476093{col 41}{space 1}   -6.28{col 50}{space 3}0.000{col 58}{space 4}-.3921891{col 71}{space 3}-.2055642
{txt}{space 11}2010  {c |}{col 18}{res}{space 2}-.0264855{col 30}{space 2} .0357982{col 41}{space 1}   -0.74{col 50}{space 3}0.459{col 58}{space 4}-.0966487{col 71}{space 3} .0436776
{txt}{space 11}2011  {c |}{col 18}{res}{space 2}-.0794912{col 30}{space 2} .0402382{col 41}{space 1}   -1.98{col 50}{space 3}0.048{col 58}{space 4}-.1583566{col 71}{space 3}-.0006258
{txt}{space 11}2012  {c |}{col 18}{res}{space 2}-.0161979{col 30}{space 2} .0361744{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-.0870984{col 71}{space 3} .0547026
{txt}{space 11}2013  {c |}{col 18}{res}{space 2} .0593277{col 30}{space 2} .0405324{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4}-.0201143{col 71}{space 3} .1387697
{txt}{space 11}2014  {c |}{col 18}{res}{space 2}-.2065195{col 30}{space 2} .0398334{col 41}{space 1}   -5.18{col 50}{space 3}0.000{col 58}{space 4}-.2845915{col 71}{space 3}-.1284475
{txt}{space 11}2015  {c |}{col 18}{res}{space 2} .1239377{col 30}{space 2} .0389841{col 41}{space 1}    3.18{col 50}{space 3}0.001{col 58}{space 4} .0475304{col 71}{space 3} .2003451
{txt}{space 11}2016  {c |}{col 18}{res}{space 2}-.2589768{col 30}{space 2} .0556829{col 41}{space 1}   -4.65{col 50}{space 3}0.000{col 58}{space 4}-.3681133{col 71}{space 3}-.1498402
{txt}{space 11}2018  {c |}{col 18}{res}{space 2} .3564348{col 30}{space 2} .0409856{col 41}{space 1}    8.70{col 50}{space 3}0.000{col 58}{space 4} .2761046{col 71}{space 3} .4367651
{txt}{space 11}2019  {c |}{col 18}{res}{space 2}-.1222194{col 30}{space 2} .0394004{col 41}{space 1}   -3.10{col 50}{space 3}0.002{col 58}{space 4}-.1994426{col 71}{space 3}-.0449961
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 0 82}Note: dy/dx for factor levels is the discrete change from the base level.{txt}{p_end}
{res}{txt}
{com}. eststo est1
{txt}
{com}. 
. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_ETHIOPIA if country==3, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-20909.917}  
Iteration 1:{space 3}log pseudolikelihood = {res:-20909.917}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   2504.92
{txt}Log pseudolikelihood = {res}-20909.917{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,555} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0131161{col 30}{space 2} .0039433{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0053874{col 71}{space 3} .0208448
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0011732{col 30}{space 2} .0001443{col 41}{space 1}   -8.13{col 50}{space 3}0.000{col 58}{space 4}-.0014561{col 71}{space 3}-.0008903
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0115654{col 30}{space 2} .0017153{col 41}{space 1}    6.74{col 50}{space 3}0.000{col 58}{space 4} .0082034{col 71}{space 3} .0149274
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} -.010769{col 30}{space 2} .0149084{col 41}{space 1}   -0.72{col 50}{space 3}0.470{col 58}{space 4}-.0399889{col 71}{space 3}  .018451
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0011677{col 30}{space 2} .0002477{col 41}{space 1}   -4.71{col 50}{space 3}0.000{col 58}{space 4}-.0016533{col 71}{space 3}-.0006822
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0089974{col 30}{space 2} .0089636{col 41}{space 1}   -1.00{col 50}{space 3}0.315{col 58}{space 4}-.0265658{col 71}{space 3} .0085709
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0904812{col 30}{space 2} .0076773{col 41}{space 1}   11.79{col 50}{space 3}0.000{col 58}{space 4}  .075434{col 71}{space 3} .1055283
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.0476634{col 30}{space 2} .0322803{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.1109317{col 71}{space 3} .0156049
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0421838{col 30}{space 2} .0089562{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .0246299{col 71}{space 3} .0597377
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0412605{col 30}{space 2} .0106654{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0203567{col 71}{space 3} .0621642
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0150074{col 30}{space 2} .0133296{col 41}{space 1}    1.13{col 50}{space 3}0.260{col 58}{space 4}-.0111181{col 71}{space 3} .0411329
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0502685{col 30}{space 2} .0114933{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .0277421{col 71}{space 3}  .072795
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0495469{col 30}{space 2} .0079096{col 41}{space 1}   -6.26{col 50}{space 3}0.000{col 58}{space 4}-.0650494{col 71}{space 3}-.0340444
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0031939{col 30}{space 2} .0008099{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .0016064{col 71}{space 3} .0047813
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0882554{col 30}{space 2} .0075946{col 41}{space 1}   11.62{col 50}{space 3}0.000{col 58}{space 4} .0733703{col 71}{space 3} .1031405
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .173892{col 30}{space 2} .0498421{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4} .0762032{col 71}{space 3} .2715807
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1025938{col 30}{space 2} .0133883{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .0763532{col 71}{space 3} .1288344
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0968291{col 30}{space 2} .0152217{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .0669951{col 71}{space 3} .1266631
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}  .094755{col 30}{space 2} .0202239{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .0551169{col 71}{space 3}  .134393
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0216547{col 30}{space 2} .0145282{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4}  -.00682{col 71}{space 3} .0501295
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0061781{col 30}{space 2} .0047471{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4} -.003126{col 71}{space 3} .0154822
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.0304289{col 30}{space 2} .0053562{col 41}{space 1}   -5.68{col 50}{space 3}0.000{col 58}{space 4}-.0409268{col 71}{space 3} -.019931
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.139897{col 30}{space 2}   .02309{col 41}{space 1}   49.37{col 50}{space 3}0.000{col 58}{space 4} 1.094642{col 71}{space 3} 1.185153
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,410
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0554832{col 30}{space 2} .0166808{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0227895{col 71}{space 3} .0881769
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0049628{col 30}{space 2} .0006114{col 41}{space 1}   -8.12{col 50}{space 3}0.000{col 58}{space 4} -.006161{col 71}{space 3}-.0037646
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0489234{col 30}{space 2} .0072528{col 41}{space 1}    6.75{col 50}{space 3}0.000{col 58}{space 4} .0347082{col 71}{space 3} .0631385
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0455543{col 30}{space 2} .0630629{col 41}{space 1}   -0.72{col 50}{space 3}0.470{col 58}{space 4}-.1691553{col 71}{space 3} .0780467
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0049397{col 30}{space 2} .0010483{col 41}{space 1}   -4.71{col 50}{space 3}0.000{col 58}{space 4}-.0069943{col 71}{space 3}-.0028852
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0380605{col 30}{space 2} .0379156{col 41}{space 1}   -1.00{col 50}{space 3}0.315{col 58}{space 4}-.1123737{col 71}{space 3} .0362526
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3827488{col 30}{space 2} .0325026{col 41}{space 1}   11.78{col 50}{space 3}0.000{col 58}{space 4} .3190449{col 71}{space 3} .4464526
{txt}{space 8}motobike {c |}{col 18}{res}{space 2}-.2016232{col 30}{space 2} .1365564{col 41}{space 1}   -1.48{col 50}{space 3}0.140{col 58}{space 4}-.4692688{col 71}{space 3} .0660223
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1784437{col 30}{space 2} .0378932{col 41}{space 1}    4.71{col 50}{space 3}0.000{col 58}{space 4} .1041744{col 71}{space 3}  .252713
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .1745379{col 30}{space 2} .0451074{col 41}{space 1}    3.87{col 50}{space 3}0.000{col 58}{space 4} .0861289{col 71}{space 3} .2629468
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0634836{col 30}{space 2} .0563849{col 41}{space 1}    1.13{col 50}{space 3}0.260{col 58}{space 4}-.0470289{col 71}{space 3}  .173996
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2126434{col 30}{space 2} .0486209{col 41}{space 1}    4.37{col 50}{space 3}0.000{col 58}{space 4} .1173482{col 71}{space 3} .3079385
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2095908{col 30}{space 2} .0334673{col 41}{space 1}   -6.26{col 50}{space 3}0.000{col 58}{space 4}-.2751855{col 71}{space 3}-.1439961
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0135106{col 30}{space 2} .0034257{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .0067964{col 71}{space 3} .0202248
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3733336{col 30}{space 2} .0321715{col 41}{space 1}   11.60{col 50}{space 3}0.000{col 58}{space 4} .3102785{col 71}{space 3} .4363886
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .7355889{col 30}{space 2} .2108395{col 41}{space 1}    3.49{col 50}{space 3}0.000{col 58}{space 4}  .322351{col 71}{space 3} 1.148827
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .433987{col 30}{space 2} .0566575{col 41}{space 1}    7.66{col 50}{space 3}0.000{col 58}{space 4} .3229403{col 71}{space 3} .5450338
{txt}electricity_mean {c |}{col 18}{res}{space 2} .4096015{col 30}{space 2} .0644286{col 41}{space 1}    6.36{col 50}{space 3}0.000{col 58}{space 4} .2833239{col 71}{space 3} .5358792
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .4008276{col 30}{space 2}  .085503{col 41}{space 1}    4.69{col 50}{space 3}0.000{col 58}{space 4} .2332448{col 71}{space 3} .5684105
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0916028{col 30}{space 2} .0614485{col 41}{space 1}    1.49{col 50}{space 3}0.136{col 58}{space 4} -.028834{col 71}{space 3} .2120395
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0261343{col 30}{space 2} .0200794{col 41}{space 1}    1.30{col 50}{space 3}0.193{col 58}{space 4}-.0132206{col 71}{space 3} .0654893
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}-.1287187{col 30}{space 2}  .022645{col 41}{space 1}   -5.68{col 50}{space 3}0.000{col 58}{space 4} -.173102{col 71}{space 3}-.0843354
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est2
{txt}
{com}. 
. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_MALAWI  if country==6, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-9227.2713}  
Iteration 1:{space 3}log pseudolikelihood = {res:-9227.2709}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}   1533.00
{txt}Log pseudolikelihood = {res}-9227.2709{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:1,571} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0066701{col 30}{space 2} .0071346{col 41}{space 1}   -0.93{col 50}{space 3}0.350{col 58}{space 4}-.0206537{col 71}{space 3} .0073134
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0007753{col 30}{space 2} .0001674{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4}-.0011034{col 71}{space 3}-.0004473
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0015596{col 30}{space 2} .0020282{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}-.0055347{col 71}{space 3} .0024155
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0468282{col 30}{space 2} .0183424{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.0827787{col 71}{space 3}-.0108777
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0003049{col 30}{space 2} .0003022{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.0008972{col 71}{space 3} .0002874
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0156842{col 30}{space 2} .0109946{col 41}{space 1}   -1.43{col 50}{space 3}0.154{col 58}{space 4}-.0372332{col 71}{space 3} .0058648
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .060917{col 30}{space 2} .0109564{col 41}{space 1}    5.56{col 50}{space 3}0.000{col 58}{space 4} .0394429{col 71}{space 3} .0823911
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0387544{col 30}{space 2} .0276856{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0155084{col 71}{space 3} .0930172
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0199406{col 30}{space 2} .0119721{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0035242{col 71}{space 3} .0434054
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0348963{col 30}{space 2} .0201776{col 41}{space 1}    1.73{col 50}{space 3}0.084{col 58}{space 4}-.0046511{col 71}{space 3} .0744437
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0233059{col 30}{space 2} .0132316{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0026276{col 71}{space 3} .0492394
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0429206{col 30}{space 2} .0093364{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4} .0246215{col 71}{space 3} .0612196
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0336784{col 30}{space 2} .0078137{col 41}{space 1}   -4.31{col 50}{space 3}0.000{col 58}{space 4} -.048993{col 71}{space 3}-.0183638
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0161029{col 30}{space 2}  .005197{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4}  .005917{col 71}{space 3} .0262888
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0108237{col 30}{space 2} .0111554{col 41}{space 1}    0.97{col 50}{space 3}0.332{col 58}{space 4}-.0110404{col 71}{space 3} .0326878
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0051572{col 30}{space 2} .0470284{col 41}{space 1}    0.11{col 50}{space 3}0.913{col 58}{space 4}-.0870168{col 71}{space 3} .0973313
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1224378{col 30}{space 2}  .018563{col 41}{space 1}    6.60{col 50}{space 3}0.000{col 58}{space 4}  .086055{col 71}{space 3} .1588205
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .108526{col 30}{space 2} .0253827{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .0587768{col 71}{space 3} .1582753
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0538891{col 30}{space 2} .0183357{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .0179518{col 71}{space 3} .0898264
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0471124{col 30}{space 2} .0164022{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0149646{col 71}{space 3} .0792601
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0014226{col 30}{space 2} .0108799{col 41}{space 1}    0.13{col 50}{space 3}0.896{col 58}{space 4}-.0199016{col 71}{space 3} .0227468
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .0437137{col 30}{space 2} .0097159{col 41}{space 1}    4.50{col 50}{space 3}0.000{col 58}{space 4} .0246709{col 71}{space 3} .0627565
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0174132{col 30}{space 2} .0085267{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0007011{col 71}{space 3} .0341253
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.707713{col 30}{space 2} .0612206{col 41}{space 1}   27.89{col 50}{space 3}0.000{col 58}{space 4} 1.587723{col 71}{space 3} 1.827703
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     4,626
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_3 year_6}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0397714{col 30}{space 2} .0425398{col 41}{space 1}   -0.93{col 50}{space 3}0.350{col 58}{space 4}-.1231479{col 71}{space 3}  .043605
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} -.004623{col 30}{space 2}  .000998{col 41}{space 1}   -4.63{col 50}{space 3}0.000{col 58}{space 4}-.0065791{col 71}{space 3} -.002667
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0092994{col 30}{space 2} .0120896{col 41}{space 1}   -0.77{col 50}{space 3}0.442{col 58}{space 4}-.0329946{col 71}{space 3} .0143958
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.2792178{col 30}{space 2} .1094899{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-.4938141{col 71}{space 3}-.0646215
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.001818{col 30}{space 2} .0018016{col 41}{space 1}   -1.01{col 50}{space 3}0.313{col 58}{space 4}-.0053491{col 71}{space 3} .0017131
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}-.0935188{col 30}{space 2} .0655182{col 41}{space 1}   -1.43{col 50}{space 3}0.153{col 58}{space 4} -.221932{col 71}{space 3} .0348945
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3632239{col 30}{space 2} .0652982{col 41}{space 1}    5.56{col 50}{space 3}0.000{col 58}{space 4} .2352418{col 71}{space 3} .4912059
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2310772{col 30}{space 2} .1651192{col 41}{space 1}    1.40{col 50}{space 3}0.162{col 58}{space 4}-.0925505{col 71}{space 3} .5547049
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1188979{col 30}{space 2} .0713755{col 41}{space 1}    1.67{col 50}{space 3}0.096{col 58}{space 4}-.0209955{col 71}{space 3} .2587913
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2080728{col 30}{space 2} .1202821{col 41}{space 1}    1.73{col 50}{space 3}0.084{col 58}{space 4}-.0276758{col 71}{space 3} .4438215
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1389636{col 30}{space 2} .0789168{col 41}{space 1}    1.76{col 50}{space 3}0.078{col 58}{space 4}-.0157104{col 71}{space 3} .2936377
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2559182{col 30}{space 2} .0556093{col 41}{space 1}    4.60{col 50}{space 3}0.000{col 58}{space 4}  .146926{col 71}{space 3} .3649104
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.2008109{col 30}{space 2} .0465949{col 41}{space 1}   -4.31{col 50}{space 3}0.000{col 58}{space 4}-.2921352{col 71}{space 3}-.1094865
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0960154{col 30}{space 2} .0310014{col 41}{space 1}    3.10{col 50}{space 3}0.002{col 58}{space 4} .0352538{col 71}{space 3} .1567771
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0645375{col 30}{space 2} .0665185{col 41}{space 1}    0.97{col 50}{space 3}0.332{col 58}{space 4}-.0658364{col 71}{space 3} .1949114
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0307505{col 30}{space 2} .2804025{col 41}{space 1}    0.11{col 50}{space 3}0.913{col 58}{space 4}-.5188284{col 71}{space 3} .5803294
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .7300478{col 30}{space 2} .1107693{col 41}{space 1}    6.59{col 50}{space 3}0.000{col 58}{space 4}  .512944{col 71}{space 3} .9471517
{txt}electricity_mean {c |}{col 18}{res}{space 2} .6470976{col 30}{space 2} .1512647{col 41}{space 1}    4.28{col 50}{space 3}0.000{col 58}{space 4} .3506242{col 71}{space 3}  .943571
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .3213193{col 30}{space 2} .1092639{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .1071661{col 71}{space 3} .5354725
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2809123{col 30}{space 2} .0978118{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0892047{col 71}{space 3} .4726199
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0084825{col 30}{space 2} .0648734{col 41}{space 1}    0.13{col 50}{space 3}0.896{col 58}{space 4}-.1186671{col 71}{space 3}  .135632
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2} .2606473{col 30}{space 2} .0578281{col 41}{space 1}    4.51{col 50}{space 3}0.000{col 58}{space 4} .1473064{col 71}{space 3} .3739882
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .103828{col 30}{space 2} .0508325{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .0041981{col 71}{space 3} .2034579
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est3
{txt}
{com}. 
. poisson hdd9 pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGER if country==1, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-13053.388}  
Iteration 1:{space 3}log pseudolikelihood = {res:-13053.388}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 49}Wald chi2({res}22{txt}){col 67}= {res}   1366.65
{txt}Log pseudolikelihood = {res}-13053.388{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:3,837} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0055981{col 30}{space 2} .0080895{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4} -.010257{col 71}{space 3} .0214533
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0000744{col 30}{space 2} .0000496{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0000228{col 71}{space 3} .0001717
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}  .002712{col 30}{space 2} .0011082{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4}   .00054{col 71}{space 3} .0048841
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0244361{col 30}{space 2}  .017908{col 41}{space 1}   -1.36{col 50}{space 3}0.172{col 58}{space 4}-.0595351{col 71}{space 3} .0106628
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0004833{col 30}{space 2} .0002616{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4}-.0000294{col 71}{space 3} .0009961
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0124155{col 30}{space 2} .0106142{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4} -.008388{col 71}{space 3} .0332189
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0632932{col 30}{space 2} .0080206{col 41}{space 1}    7.89{col 50}{space 3}0.000{col 58}{space 4} .0475732{col 71}{space 3} .0790133
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0555689{col 30}{space 2} .0183082{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .0196855{col 71}{space 3} .0914523
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0204619{col 30}{space 2} .0145357{col 41}{space 1}    1.41{col 50}{space 3}0.159{col 58}{space 4}-.0080277{col 71}{space 3} .0489514
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0443577{col 30}{space 2} .0205212{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0041369{col 71}{space 3} .0845785
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0382714{col 30}{space 2} .0156243{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0076483{col 71}{space 3} .0688945
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.0277075{col 30}{space 2} .0127963{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.0527879{col 71}{space 3}-.0026271
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0251433{col 30}{space 2} .0085496{col 41}{space 1}   -2.94{col 50}{space 3}0.003{col 58}{space 4}-.0419002{col 71}{space 3}-.0083864
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0002753{col 30}{space 2} .0002921{col 41}{space 1}   -0.94{col 50}{space 3}0.346{col 58}{space 4}-.0008478{col 71}{space 3} .0002972
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0354692{col 30}{space 2} .0372856{col 41}{space 1}    0.95{col 50}{space 3}0.341{col 58}{space 4}-.0376093{col 71}{space 3} .1085476
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0040511{col 30}{space 2} .0219898{col 41}{space 1}   -0.18{col 50}{space 3}0.854{col 58}{space 4}-.0471504{col 71}{space 3} .0390482
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .058851{col 30}{space 2} .0176491{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .0242594{col 71}{space 3} .0934426
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0691507{col 30}{space 2} .0231331{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .0238107{col 71}{space 3} .1144908
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0280009{col 30}{space 2} .0191203{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4}-.0094741{col 71}{space 3} .0654759
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0755268{col 30}{space 2} .0155407{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .0450677{col 71}{space 3} .1059859
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0118139{col 30}{space 2} .0098427{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.0074775{col 71}{space 3} .0311053
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .0414984{col 30}{space 2} .0069785{col 41}{space 1}    5.95{col 50}{space 3}0.000{col 58}{space 4} .0278209{col 71}{space 3}  .055176
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.409321{col 30}{space 2} .0379188{col 41}{space 1}   37.17{col 50}{space 3}0.000{col 58}{space 4} 1.335002{col 71}{space 3} 1.483641
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}     6,536
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_4}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0314947{col 30}{space 2} .0455135{col 41}{space 1}    0.69{col 50}{space 3}0.489{col 58}{space 4}-.0577102{col 71}{space 3} .1206996
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0004188{col 30}{space 2}  .000279{col 41}{space 1}    1.50{col 50}{space 3}0.133{col 58}{space 4}-.0001281{col 71}{space 3} .0009657
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0152576{col 30}{space 2} .0062327{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0030417{col 71}{space 3} .0274736
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.1374757{col 30}{space 2} .1007619{col 41}{space 1}   -1.36{col 50}{space 3}0.172{col 58}{space 4}-.3349654{col 71}{space 3} .0600139
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0027192{col 30}{space 2} .0014717{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4}-.0001652{col 71}{space 3} .0056036
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0698483{col 30}{space 2} .0597149{col 41}{space 1}    1.17{col 50}{space 3}0.242{col 58}{space 4}-.0471907{col 71}{space 3} .1868873
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3560826{col 30}{space 2} .0450692{col 41}{space 1}    7.90{col 50}{space 3}0.000{col 58}{space 4} .2677485{col 71}{space 3} .4444166
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .3126259{col 30}{space 2} .1029647{col 41}{space 1}    3.04{col 50}{space 3}0.002{col 58}{space 4} .1108188{col 71}{space 3}  .514433
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1151167{col 30}{space 2} .0817689{col 41}{space 1}    1.41{col 50}{space 3}0.159{col 58}{space 4}-.0451473{col 71}{space 3} .2753808
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .2495527{col 30}{space 2} .1154367{col 41}{space 1}    2.16{col 50}{space 3}0.031{col 58}{space 4} .0233009{col 71}{space 3} .4758046
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2153117{col 30}{space 2} .0879039{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .0430232{col 71}{space 3} .3876003
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}-.1558801{col 30}{space 2} .0719758{col 41}{space 1}   -2.17{col 50}{space 3}0.030{col 58}{space 4}-.2969501{col 71}{space 3}-.0148102
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1414542{col 30}{space 2} .0481142{col 41}{space 1}   -2.94{col 50}{space 3}0.003{col 58}{space 4}-.2357563{col 71}{space 3}-.0471521
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} -.001549{col 30}{space 2} .0016434{col 41}{space 1}   -0.94{col 50}{space 3}0.346{col 58}{space 4}-.0047699{col 71}{space 3}  .001672
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .1995468{col 30}{space 2} .2097648{col 41}{space 1}    0.95{col 50}{space 3}0.341{col 58}{space 4}-.2115848{col 71}{space 3} .6106783
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}-.0227909{col 30}{space 2} .1237116{col 41}{space 1}   -0.18{col 50}{space 3}0.854{col 58}{space 4}-.2652612{col 71}{space 3} .2196794
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .331091{col 30}{space 2} .0992862{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} .1364937{col 71}{space 3} .5256883
{txt}electricity_mean {c |}{col 18}{res}{space 2} .3890363{col 30}{space 2} .1301325{col 41}{space 1}    2.99{col 50}{space 3}0.003{col 58}{space 4} .1339813{col 71}{space 3} .6440914
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .1575307{col 30}{space 2}  .107563{col 41}{space 1}    1.46{col 50}{space 3}0.143{col 58}{space 4}-.0532889{col 71}{space 3} .3683503
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .4249075{col 30}{space 2} .0873621{col 41}{space 1}    4.86{col 50}{space 3}0.000{col 58}{space 4} .2536809{col 71}{space 3} .5961342
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}  .066464{col 30}{space 2} .0553643{col 41}{space 1}    1.20{col 50}{space 3}0.230{col 58}{space 4}-.0420479{col 71}{space 3}  .174976
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2} .2334667{col 30}{space 2} .0391659{col 41}{space 1}    5.96{col 50}{space 3}0.000{col 58}{space 4} .1567029{col 71}{space 3} .3102305
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est4
{txt}
{com}. 
. 
. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_NIGERIA if country==2, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-30000.802}  
Iteration 1:{space 3}log pseudolikelihood = {res:-30000.802}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   3907.19
{txt}Log pseudolikelihood = {res}-30000.802{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:7,154} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0183805{col 30}{space 2} .0035099{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0115012{col 71}{space 3} .0252597
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0005724{col 30}{space 2} .0000613{col 41}{space 1}   -9.34{col 50}{space 3}0.000{col 58}{space 4}-.0006925{col 71}{space 3}-.0004523
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0043722{col 30}{space 2} .0008418{col 41}{space 1}   -5.19{col 50}{space 3}0.000{col 58}{space 4}-.0060222{col 71}{space 3}-.0027223
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0223503{col 30}{space 2} .0095779{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4} .0035779{col 71}{space 3} .0411226
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0010496{col 30}{space 2}  .000173{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .0007105{col 71}{space 3} .0013887
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0643076{col 30}{space 2} .0067426{col 41}{space 1}    9.54{col 50}{space 3}0.000{col 58}{space 4} .0510924{col 71}{space 3} .0775228
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0452149{col 30}{space 2} .0053472{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .0347346{col 71}{space 3} .0556952
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0031255{col 30}{space 2} .0072879{col 41}{space 1}    0.43{col 50}{space 3}0.668{col 58}{space 4}-.0111586{col 71}{space 3} .0174095
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0321867{col 30}{space 2} .0075521{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4}  .017385{col 71}{space 3} .0469885
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0140425{col 30}{space 2} .0083828{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0023874{col 71}{space 3} .0304725
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2}  .040333{col 30}{space 2} .0093426{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0220219{col 71}{space 3} .0586441
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0542093{col 30}{space 2} .0076173{col 41}{space 1}    7.12{col 50}{space 3}0.000{col 58}{space 4} .0392797{col 71}{space 3} .0691389
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0019711{col 30}{space 2} .0085859{col 41}{space 1}    0.23{col 50}{space 3}0.818{col 58}{space 4}-.0148569{col 71}{space 3} .0187991
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0019784{col 30}{space 2} .0014984{col 41}{space 1}   -1.32{col 50}{space 3}0.187{col 58}{space 4}-.0049153{col 71}{space 3} .0009584
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0554389{col 30}{space 2} .0099194{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .0359973{col 71}{space 3} .0748804
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0213736{col 30}{space 2} .0096583{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0024436{col 71}{space 3} .0403036
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .1432577{col 30}{space 2} .0110849{col 41}{space 1}   12.92{col 50}{space 3}0.000{col 58}{space 4} .1215317{col 71}{space 3} .1649836
{txt}electricity_mean {c |}{col 18}{res}{space 2} .1297289{col 30}{space 2}  .010416{col 41}{space 1}   12.45{col 50}{space 3}0.000{col 58}{space 4} .1093138{col 71}{space 3} .1501439
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0142371{col 30}{space 2} .0120471{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0093747{col 71}{space 3} .0378489
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}  -.01991{col 30}{space 2} .0096757{col 41}{space 1}   -2.06{col 50}{space 3}0.040{col 58}{space 4} -.038874{col 71}{space 3} -.000946
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0104618{col 30}{space 2} .0046472{col 41}{space 1}   -2.25{col 50}{space 3}0.024{col 58}{space 4}-.0195702{col 71}{space 3}-.0013534
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}  -.09735{col 30}{space 2} .0061435{col 41}{space 1}  -15.85{col 50}{space 3}0.000{col 58}{space 4}-.1093911{col 71}{space 3}-.0853089
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.0880686{col 30}{space 2} .0062907{col 41}{space 1}  -14.00{col 50}{space 3}0.000{col 58}{space 4}-.1003982{col 71}{space 3} -.075739
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.0637996{col 30}{space 2} .0062751{col 41}{space 1}  -10.17{col 50}{space 3}0.000{col 58}{space 4}-.0760986{col 71}{space 3}-.0515007
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.517068{col 30}{space 2} .0287521{col 41}{space 1}   52.76{col 50}{space 3}0.000{col 58}{space 4} 1.460715{col 71}{space 3} 1.573421
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    15,063
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_3 year_5 year_8}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .1070041{col 30}{space 2} .0204374{col 41}{space 1}    5.24{col 50}{space 3}0.000{col 58}{space 4} .0669476{col 71}{space 3} .1470606
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0033322{col 30}{space 2} .0003563{col 41}{space 1}   -9.35{col 50}{space 3}0.000{col 58}{space 4}-.0040305{col 71}{space 3}-.0026339
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0254535{col 30}{space 2} .0049039{col 41}{space 1}   -5.19{col 50}{space 3}0.000{col 58}{space 4} -.035065{col 71}{space 3}-.0158421
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .1301148{col 30}{space 2} .0557591{col 41}{space 1}    2.33{col 50}{space 3}0.020{col 58}{space 4}  .020829{col 71}{space 3} .2394006
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} .0061102{col 30}{space 2} .0010071{col 41}{space 1}    6.07{col 50}{space 3}0.000{col 58}{space 4} .0041363{col 71}{space 3}  .008084
{txt}{space 5}female_head {c |}{col 18}{res}{space 2}  .374374{col 30}{space 2} .0391946{col 41}{space 1}    9.55{col 50}{space 3}0.000{col 58}{space 4}  .297554{col 71}{space 3}  .451194
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .2632238{col 30}{space 2}   .03113{col 41}{space 1}    8.46{col 50}{space 3}0.000{col 58}{space 4} .2022101{col 71}{space 3} .3242375
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0181954{col 30}{space 2} .0424274{col 41}{space 1}    0.43{col 50}{space 3}0.668{col 58}{space 4}-.0649607{col 71}{space 3} .1013515
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .1873788{col 30}{space 2}  .043959{col 41}{space 1}    4.26{col 50}{space 3}0.000{col 58}{space 4} .1012207{col 71}{space 3}  .273537
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0817503{col 30}{space 2} .0488005{col 41}{space 1}    1.68{col 50}{space 3}0.094{col 58}{space 4}-.0138969{col 71}{space 3} .1773974
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .2348031{col 30}{space 2}  .054374{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4}  .128232{col 71}{space 3} .3413743
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .3155858{col 30}{space 2} .0443393{col 41}{space 1}    7.12{col 50}{space 3}0.000{col 58}{space 4} .2286824{col 71}{space 3} .4024892
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2} .0114751{col 30}{space 2} .0499831{col 41}{space 1}    0.23{col 50}{space 3}0.818{col 58}{space 4}-.0864899{col 71}{space 3} .1094402
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2}-.0115177{col 30}{space 2} .0087232{col 41}{space 1}   -1.32{col 50}{space 3}0.187{col 58}{space 4}-.0286149{col 71}{space 3} .0055795
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .3227438{col 30}{space 2} .0577357{col 41}{space 1}    5.59{col 50}{space 3}0.000{col 58}{space 4} .2095839{col 71}{space 3} .4359038
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .1244289{col 30}{space 2} .0562296{col 41}{space 1}    2.21{col 50}{space 3}0.027{col 58}{space 4} .0142208{col 71}{space 3}  .234637
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2}  .833991{col 30}{space 2} .0645204{col 41}{space 1}   12.93{col 50}{space 3}0.000{col 58}{space 4} .7075333{col 71}{space 3} .9604488
{txt}electricity_mean {c |}{col 18}{res}{space 2} .7552317{col 30}{space 2} .0606593{col 41}{space 1}   12.45{col 50}{space 3}0.000{col 58}{space 4} .6363416{col 71}{space 3} .8741218
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0828829{col 30}{space 2} .0701373{col 41}{space 1}    1.18{col 50}{space 3}0.237{col 58}{space 4}-.0545837{col 71}{space 3} .2203494
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2}-.1159083{col 30}{space 2} .0563331{col 41}{space 1}   -2.06{col 50}{space 3}0.040{col 58}{space 4}-.2263193{col 71}{space 3}-.0054974
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2}-.0609046{col 30}{space 2} .0270587{col 41}{space 1}   -2.25{col 50}{space 3}0.024{col 58}{space 4}-.1139387{col 71}{space 3}-.0078704
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.5667343{col 30}{space 2} .0356379{col 41}{space 1}  -15.90{col 50}{space 3}0.000{col 58}{space 4}-.6365833{col 71}{space 3}-.4968853
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}-.5127014{col 30}{space 2} .0364593{col 41}{space 1}  -14.06{col 50}{space 3}0.000{col 58}{space 4}-.5841603{col 71}{space 3}-.4412425
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2}-.3714171{col 30}{space 2} .0364302{col 41}{space 1}  -10.20{col 50}{space 3}0.000{col 58}{space 4}-.4428189{col 71}{space 3}-.3000153
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est5
{txt}
{com}. 
. 
. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_TANZANIA if country==5, cluster(HHID_panel)
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-23411.484}  
Iteration 1:{space 3}log pseudolikelihood = {res:-23411.484}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 49}Wald chi2({res}24{txt}){col 67}= {res}   1880.55
{txt}Log pseudolikelihood = {res}-23411.484{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:5,710} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0065777{col 30}{space 2} .0046252{col 41}{space 1}   -1.42{col 50}{space 3}0.155{col 58}{space 4}-.0156429{col 71}{space 3} .0024875
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}  .000124{col 30}{space 2} .0001905{col 41}{space 1}    0.65{col 50}{space 3}0.515{col 58}{space 4}-.0002494{col 71}{space 3} .0004973
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0006853{col 30}{space 2} .0010099{col 41}{space 1}   -0.68{col 50}{space 3}0.497{col 58}{space 4}-.0026646{col 71}{space 3} .0012939
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0055779{col 30}{space 2} .0122068{col 41}{space 1}   -0.46{col 50}{space 3}0.648{col 58}{space 4}-.0295029{col 71}{space 3}  .018347
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0000761{col 30}{space 2} .0001911{col 41}{space 1}   -0.40{col 50}{space 3}0.690{col 58}{space 4}-.0004507{col 71}{space 3} .0002985
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0068789{col 30}{space 2} .0067616{col 41}{space 1}    1.02{col 50}{space 3}0.309{col 58}{space 4}-.0063735{col 71}{space 3} .0201314
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0564765{col 30}{space 2} .0067338{col 41}{space 1}    8.39{col 50}{space 3}0.000{col 58}{space 4} .0432784{col 71}{space 3} .0696746
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0399285{col 30}{space 2} .0136366{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0132012{col 71}{space 3} .0666557
{txt}{space 11}phone {c |}{col 18}{res}{space 2}  .051673{col 30}{space 2} .0089542{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .0341232{col 71}{space 3} .0692229
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0021604{col 30}{space 2} .0095021{col 41}{space 1}    0.23{col 50}{space 3}0.820{col 58}{space 4}-.0164635{col 71}{space 3} .0207842
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0247953{col 30}{space 2} .0068825{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0113058{col 71}{space 3} .0382848
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .042027{col 30}{space 2} .0071327{col 41}{space 1}    5.89{col 50}{space 3}0.000{col 58}{space 4} .0280471{col 71}{space 3} .0560069
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0339475{col 30}{space 2} .0062768{col 41}{space 1}   -5.41{col 50}{space 3}0.000{col 58}{space 4}-.0462498{col 71}{space 3}-.0216451
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0001772{col 30}{space 2} .0006041{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.0010068{col 71}{space 3} .0013612
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0287852{col 30}{space 2} .0058395{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4}   .01734{col 71}{space 3} .0402303
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0417883{col 30}{space 2} .0178818{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0067406{col 71}{space 3} .0768361
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0839493{col 30}{space 2} .0122215{col 41}{space 1}    6.87{col 50}{space 3}0.000{col 58}{space 4} .0599955{col 71}{space 3}  .107903
{txt}electricity_mean {c |}{col 18}{res}{space 2} .0971483{col 30}{space 2} .0123325{col 41}{space 1}    7.88{col 50}{space 3}0.000{col 58}{space 4}  .072977{col 71}{space 3} .1213195
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0054343{col 30}{space 2} .0097961{col 41}{space 1}   -0.55{col 50}{space 3}0.579{col 58}{space 4}-.0246343{col 71}{space 3} .0137657
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0383213{col 30}{space 2} .0100351{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .0186527{col 71}{space 3} .0579898
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0157923{col 30}{space 2} .0059427{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0041448{col 71}{space 3} .0274398
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .0203544{col 30}{space 2} .0070884{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0064614{col 71}{space 3} .0342474
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2}  .017492{col 30}{space 2}  .006146{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} .0054461{col 71}{space 3} .0295379
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0031422{col 30}{space 2} .0062628{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0091326{col 71}{space 3}  .015417
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 1.464948{col 30}{space 2} .0300157{col 41}{space 1}   48.81{col 50}{space 3}0.000{col 58}{space 4} 1.406119{col 71}{space 3} 1.523778
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post  
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    11,830
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_1 year_5 year_7}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2}-.0376335{col 30}{space 2} .0264608{col 41}{space 1}   -1.42{col 50}{space 3}0.155{col 58}{space 4}-.0894958{col 71}{space 3} .0142287
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} .0007092{col 30}{space 2} .0010898{col 41}{space 1}    0.65{col 50}{space 3}0.515{col 58}{space 4}-.0014267{col 71}{space 3} .0028451
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2}-.0039211{col 30}{space 2} .0057782{col 41}{space 1}   -0.68{col 50}{space 3}0.497{col 58}{space 4}-.0152462{col 71}{space 3}  .007404
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2}-.0319135{col 30}{space 2} .0698432{col 41}{space 1}   -0.46{col 50}{space 3}0.648{col 58}{space 4}-.1688037{col 71}{space 3} .1049766
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0004355{col 30}{space 2} .0010934{col 41}{space 1}   -0.40{col 50}{space 3}0.690{col 58}{space 4}-.0025785{col 71}{space 3} .0017075
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0393571{col 30}{space 2} .0386882{col 41}{space 1}    1.02{col 50}{space 3}0.309{col 58}{space 4}-.0364703{col 71}{space 3} .1151845
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .3231239{col 30}{space 2} .0385481{col 41}{space 1}    8.38{col 50}{space 3}0.000{col 58}{space 4} .2475711{col 71}{space 3} .3986768
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .2284462{col 30}{space 2} .0780142{col 41}{space 1}    2.93{col 50}{space 3}0.003{col 58}{space 4} .0755412{col 71}{space 3} .3813511
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2956414{col 30}{space 2} .0512258{col 41}{space 1}    5.77{col 50}{space 3}0.000{col 58}{space 4} .1952406{col 71}{space 3} .3960422
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0123604{col 30}{space 2} .0543649{col 41}{space 1}    0.23{col 50}{space 3}0.820{col 58}{space 4} -.094193{col 71}{space 3} .1189137
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .1418636{col 30}{space 2} .0393687{col 41}{space 1}    3.60{col 50}{space 3}0.000{col 58}{space 4} .0647024{col 71}{space 3} .2190249
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .2404528{col 30}{space 2} .0408126{col 41}{space 1}    5.89{col 50}{space 3}0.000{col 58}{space 4} .1604616{col 71}{space 3} .3204441
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.1942265{col 30}{space 2} .0359137{col 41}{space 1}   -5.41{col 50}{space 3}0.000{col 58}{space 4}-.2646161{col 71}{space 3}-.1238369
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0010136{col 30}{space 2} .0034563{col 41}{space 1}    0.29{col 50}{space 3}0.769{col 58}{space 4}-.0057605{col 71}{space 3} .0077877
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2}  .164691{col 30}{space 2} .0334148{col 41}{space 1}    4.93{col 50}{space 3}0.000{col 58}{space 4} .0991993{col 71}{space 3} .2301828
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .2390872{col 30}{space 2} .1023207{col 41}{space 1}    2.34{col 50}{space 3}0.019{col 58}{space 4} .0385422{col 71}{space 3} .4396322
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .4803062{col 30}{space 2} .0699257{col 41}{space 1}    6.87{col 50}{space 3}0.000{col 58}{space 4} .3432543{col 71}{space 3} .6173581
{txt}electricity_mean {c |}{col 18}{res}{space 2} .5558228{col 30}{space 2} .0705172{col 41}{space 1}    7.88{col 50}{space 3}0.000{col 58}{space 4} .4176116{col 71}{space 3} .6940339
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2}-.0310918{col 30}{space 2} .0560455{col 41}{space 1}   -0.55{col 50}{space 3}0.579{col 58}{space 4}-.1409389{col 71}{space 3} .0787553
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2192507{col 30}{space 2} .0573961{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .1067565{col 71}{space 3} .3317449
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0903538{col 30}{space 2} .0340047{col 41}{space 1}    2.66{col 50}{space 3}0.008{col 58}{space 4} .0237057{col 71}{space 3} .1570018
{txt}{space 10}year_1 {c |}{col 18}{res}{space 2} .1164553{col 30}{space 2} .0405682{col 41}{space 1}    2.87{col 50}{space 3}0.004{col 58}{space 4} .0369431{col 71}{space 3} .1959675
{txt}{space 10}year_5 {c |}{col 18}{res}{space 2} .1000784{col 30}{space 2} .0351677{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4}  .031151{col 71}{space 3} .1690058
{txt}{space 10}year_7 {c |}{col 18}{res}{space 2} .0179779{col 30}{space 2} .0358283{col 41}{space 1}    0.50{col 50}{space 3}0.616{col 58}{space 4}-.0522442{col 71}{space 3}    .0882
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est6
{txt}
{com}. 
. 
. poisson hdd9  pdd9_dist  sum_dist  $xlist pdd9_mean_dist $year_UGANDA if country==4, cluster(HHID_panel) 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-31898.792}  
Iteration 1:{space 3}log pseudolikelihood = {res:-31898.792}  
{res}
{txt}Poisson regression{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 49}Wald chi2({res}26{txt}){col 67}= {res}   2293.61
{txt}Log pseudolikelihood = {res}-31898.792{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000

{txt}{ralign 82:(Std. Err. adjusted for {res:4,402} clusters in HHID_panel)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}            hdd9{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0036363{col 30}{space 2} .0031954{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0026266{col 71}{space 3} .0098992
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2}-.0001617{col 30}{space 2} .0001769{col 41}{space 1}   -0.91{col 50}{space 3}0.361{col 58}{space 4}-.0005084{col 71}{space 3} .0001849
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0055207{col 30}{space 2} .0009845{col 41}{space 1}    5.61{col 50}{space 3}0.000{col 58}{space 4} .0035912{col 71}{space 3} .0074502
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0021451{col 30}{space 2} .0117493{col 41}{space 1}    0.18{col 50}{space 3}0.855{col 58}{space 4}-.0208831{col 71}{space 3} .0251733
{txt}{space 8}head_age {c |}{col 18}{res}{space 2} -.000255{col 30}{space 2} .0001902{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.0006277{col 71}{space 3} .0001177
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0045102{col 30}{space 2}  .006449{col 41}{space 1}    0.70{col 50}{space 3}0.484{col 58}{space 4}-.0081295{col 71}{space 3} .0171499
{txt}{space 7}head_read {c |}{col 18}{res}{space 2} .0689116{col 30}{space 2} .0065736{col 41}{space 1}   10.48{col 50}{space 3}0.000{col 58}{space 4} .0560275{col 71}{space 3} .0817958
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .0353136{col 30}{space 2} .0091465{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4} .0173868{col 71}{space 3} .0532404
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .0465518{col 30}{space 2} .0070188{col 41}{space 1}    6.63{col 50}{space 3}0.000{col 58}{space 4} .0327952{col 71}{space 3} .0603084
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .0562951{col 30}{space 2} .0064829{col 41}{space 1}    8.68{col 50}{space 3}0.000{col 58}{space 4} .0435889{col 71}{space 3} .0690013
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0059262{col 30}{space 2} .0054759{col 41}{space 1}    1.08{col 50}{space 3}0.279{col 58}{space 4}-.0048064{col 71}{space 3} .0166587
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2} .0357563{col 30}{space 2} .0057365{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .0245131{col 71}{space 3} .0469996
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0005541{col 30}{space 2} .0049424{col 41}{space 1}   -0.11{col 50}{space 3}0.911{col 58}{space 4}-.0102411{col 71}{space 3} .0091329
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0008454{col 30}{space 2} .0003931{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0000749{col 71}{space 3} .0016159
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0100173{col 30}{space 2} .0054162{col 41}{space 1}    1.85{col 50}{space 3}0.064{col 58}{space 4}-.0005981{col 71}{space 3} .0206328
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2}  .013244{col 30}{space 2} .0140688{col 41}{space 1}    0.94{col 50}{space 3}0.347{col 58}{space 4}-.0143304{col 71}{space 3} .0408184
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .0588108{col 30}{space 2} .0116597{col 41}{space 1}    5.04{col 50}{space 3}0.000{col 58}{space 4} .0359582{col 71}{space 3} .0816634
{txt}electricity_mean {c |}{col 18}{res}{space 2}  .048162{col 30}{space 2} .0115992{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .0254279{col 71}{space 3} .0708961
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0092493{col 30}{space 2} .0099705{col 41}{space 1}    0.93{col 50}{space 3}0.354{col 58}{space 4}-.0102926{col 71}{space 3} .0287912
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .0505978{col 30}{space 2} .0095636{col 41}{space 1}    5.29{col 50}{space 3}0.000{col 58}{space 4} .0318535{col 71}{space 3} .0693421
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .0426315{col 30}{space 2} .0056948{col 41}{space 1}    7.49{col 50}{space 3}0.000{col 58}{space 4} .0314698{col 71}{space 3} .0537931
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.0307224{col 30}{space 2}  .007524{col 41}{space 1}   -4.08{col 50}{space 3}0.000{col 58}{space 4}-.0454691{col 71}{space 3}-.0159757
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.0184345{col 30}{space 2} .0064689{col 41}{space 1}   -2.85{col 50}{space 3}0.004{col 58}{space 4}-.0311133{col 71}{space 3}-.0057556
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2} .0604398{col 30}{space 2} .0061921{col 41}{space 1}    9.76{col 50}{space 3}0.000{col 58}{space 4} .0483035{col 71}{space 3}  .072576
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .0192876{col 30}{space 2} .0063177{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0069052{col 71}{space 3}   .03167
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .0532008{col 30}{space 2} .0057781{col 41}{space 1}    9.21{col 50}{space 3}0.000{col 58}{space 4}  .041876{col 71}{space 3} .0645256
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  1.15621{col 30}{space 2} .0354336{col 41}{space 1}   32.63{col 50}{space 3}0.000{col 58}{space 4} 1.086762{col 71}{space 3} 1.225659
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. margins, dydx(*) post 
{res}
{txt}Average marginal effects{col 49}Number of obs{col 67}= {res}    16,114
{txt}{col 1}Model VCE{col 14}: {res}Robust

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Predicted number of events, predict()}{p_end}
{p2colreset}{...}
{txt}{p2colset 1 14 16 2}{...}
{p2col:dy/dx w.r.t.}:{space 1}{res:pdd9_dist sum_dist hhsize dependent_share head_age female_head head_read motobike phone electricity wagejob enterprise weather_shock plot_area other_crop motobike_mean phone_mean electricity_mean wagejob_mean enterprise_mean pdd9_mean_dist year_3 year_4 year_6 year_8 year_10}{p_end}
{p2colreset}{...}

{res}{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30} Delta-method
{col 18}{c |}      dy/dx{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 7}pdd9_dist {c |}{col 18}{res}{space 2} .0203243{col 30}{space 2} .0178594{col 41}{space 1}    1.14{col 50}{space 3}0.255{col 58}{space 4}-.0146795{col 71}{space 3} .0553281
{txt}{space 8}sum_dist {c |}{col 18}{res}{space 2} -.000904{col 30}{space 2} .0009886{col 41}{space 1}   -0.91{col 50}{space 3}0.360{col 58}{space 4}-.0028416{col 71}{space 3} .0010335
{txt}{space 10}hhsize {c |}{col 18}{res}{space 2} .0308569{col 30}{space 2} .0055005{col 41}{space 1}    5.61{col 50}{space 3}0.000{col 58}{space 4} .0200762{col 71}{space 3} .0416376
{txt}{space 1}dependent_share {c |}{col 18}{res}{space 2} .0119897{col 30}{space 2} .0656698{col 41}{space 1}    0.18{col 50}{space 3}0.855{col 58}{space 4}-.1167208{col 71}{space 3} .1407002
{txt}{space 8}head_age {c |}{col 18}{res}{space 2}-.0014252{col 30}{space 2} .0010629{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-.0035085{col 71}{space 3}  .000658
{txt}{space 5}female_head {c |}{col 18}{res}{space 2} .0252089{col 30}{space 2} .0360448{col 41}{space 1}    0.70{col 50}{space 3}0.484{col 58}{space 4}-.0454377{col 71}{space 3} .0958555
{txt}{space 7}head_read {c |}{col 18}{res}{space 2}  .385168{col 30}{space 2} .0367307{col 41}{space 1}   10.49{col 50}{space 3}0.000{col 58}{space 4} .3131771{col 71}{space 3} .4571588
{txt}{space 8}motobike {c |}{col 18}{res}{space 2} .1973783{col 30}{space 2} .0511118{col 41}{space 1}    3.86{col 50}{space 3}0.000{col 58}{space 4}  .097201{col 71}{space 3} .2975555
{txt}{space 11}phone {c |}{col 18}{res}{space 2} .2601919{col 30}{space 2} .0392047{col 41}{space 1}    6.64{col 50}{space 3}0.000{col 58}{space 4} .1833521{col 71}{space 3} .3370317
{txt}{space 5}electricity {c |}{col 18}{res}{space 2} .3146502{col 30}{space 2} .0362249{col 41}{space 1}    8.69{col 50}{space 3}0.000{col 58}{space 4} .2436506{col 71}{space 3} .3856498
{txt}{space 9}wagejob {c |}{col 18}{res}{space 2} .0331231{col 30}{space 2} .0306096{col 41}{space 1}    1.08{col 50}{space 3}0.279{col 58}{space 4}-.0268706{col 71}{space 3} .0931168
{txt}{space 6}enterprise {c |}{col 18}{res}{space 2}  .199853{col 30}{space 2} .0320724{col 41}{space 1}    6.23{col 50}{space 3}0.000{col 58}{space 4} .1369923{col 71}{space 3} .2627137
{txt}{space 3}weather_shock {c |}{col 18}{res}{space 2}-.0030969{col 30}{space 2}  .027625{col 41}{space 1}   -0.11{col 50}{space 3}0.911{col 58}{space 4} -.057241{col 71}{space 3} .0510472
{txt}{space 7}plot_area {c |}{col 18}{res}{space 2} .0047251{col 30}{space 2} .0021977{col 41}{space 1}    2.15{col 50}{space 3}0.032{col 58}{space 4} .0004178{col 71}{space 3} .0090325
{txt}{space 6}other_crop {c |}{col 18}{res}{space 2} .0559898{col 30}{space 2} .0302739{col 41}{space 1}    1.85{col 50}{space 3}0.064{col 58}{space 4} -.003346{col 71}{space 3} .1153257
{txt}{space 3}motobike_mean {c |}{col 18}{res}{space 2} .0740245{col 30}{space 2} .0786364{col 41}{space 1}    0.94{col 50}{space 3}0.347{col 58}{space 4}   -.0801{col 71}{space 3}  .228149
{txt}{space 6}phone_mean {c |}{col 18}{res}{space 2} .3287113{col 30}{space 2} .0651378{col 41}{space 1}    5.05{col 50}{space 3}0.000{col 58}{space 4} .2010436{col 71}{space 3}  .456379
{txt}electricity_mean {c |}{col 18}{res}{space 2} .2691922{col 30}{space 2} .0647994{col 41}{space 1}    4.15{col 50}{space 3}0.000{col 58}{space 4} .1421877{col 71}{space 3} .3961966
{txt}{space 4}wagejob_mean {c |}{col 18}{res}{space 2} .0516971{col 30}{space 2} .0557341{col 41}{space 1}    0.93{col 50}{space 3}0.354{col 58}{space 4}-.0575397{col 71}{space 3} .1609339
{txt}{space 1}enterprise_mean {c |}{col 18}{res}{space 2} .2828062{col 30}{space 2} .0534545{col 41}{space 1}    5.29{col 50}{space 3}0.000{col 58}{space 4} .1780373{col 71}{space 3} .3875751
{txt}{space 2}pdd9_mean_dist {c |}{col 18}{res}{space 2} .2382801{col 30}{space 2} .0317886{col 41}{space 1}    7.50{col 50}{space 3}0.000{col 58}{space 4} .1759755{col 71}{space 3} .3005846
{txt}{space 10}year_3 {c |}{col 18}{res}{space 2}-.1717166{col 30}{space 2} .0420225{col 41}{space 1}   -4.09{col 50}{space 3}0.000{col 58}{space 4}-.2540791{col 71}{space 3}-.0893541
{txt}{space 10}year_4 {c |}{col 18}{res}{space 2}-.1030359{col 30}{space 2} .0361648{col 41}{space 1}   -2.85{col 50}{space 3}0.004{col 58}{space 4}-.1739176{col 71}{space 3}-.0321541
{txt}{space 10}year_6 {c |}{col 18}{res}{space 2}  .337816{col 30}{space 2}  .034577{col 41}{space 1}    9.77{col 50}{space 3}0.000{col 58}{space 4} .2700463{col 71}{space 3} .4055857
{txt}{space 10}year_8 {c |}{col 18}{res}{space 2} .1078043{col 30}{space 2} .0353022{col 41}{space 1}    3.05{col 50}{space 3}0.002{col 58}{space 4} .0386133{col 71}{space 3} .1769953
{txt}{space 9}year_10 {c |}{col 18}{res}{space 2} .2973552{col 30}{space 2} .0323016{col 41}{space 1}    9.21{col 50}{space 3}0.000{col 58}{space 4} .2340452{col 71}{space 3} .3606652
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. eststo est7
{txt}
{com}. esttab using  S27_poisson.rtf, se replace star(* 0.1 ** 0.05 *** 0.01) cells (b(star fmt(%9.3f)) se (par(( )) fmt(%9.3f)))  stats(N r2_b  r2_w r2_o p, fmt(%4.0f %4.3f %4.3f %6.3f)) keep(pdd9_dist    $xlist  pdd9_mean_dist sum_dist)
{res}{txt}(note: file S27_poisson.rtf not found)
(output written to {browse  `"S27_poisson.rtf"'})

{com}. restore
{txt}
{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\lSMS ISA\dofile\Submission\S20_S27_FE_PoissonCRE.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Apr 2024, 11:17:53
{txt}{.-}
{smcl}
{txt}{sf}{ul off}